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Işık EB, Brazas MD, Schwartz R, Gaeta B, Palagi PM, van Gelder CWG, Suravajhala P, Singh H, Morgan SL, Zahroh H, Ling M, Satagopam VP, McGrath A, Nakai K, Tan TW, Gao G, Mulder N, Schönbach C, Zheng Y, De Las Rivas J, Khan AM. Grand challenges in bioinformatics education and training. Nat Biotechnol 2023; 41:1171-1174. [PMID: 37568018 DOI: 10.1038/s41587-023-01891-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/13/2023]
Affiliation(s)
- Esra Büşra Işık
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Istanbul, Turkey
- APBioNET.org, Singapore, Singapore
| | - Michelle D Brazas
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Bioinformatics.ca, Toronto, Ontario, Canada
| | | | - Bruno Gaeta
- School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia
| | | | | | - Prashanth Suravajhala
- Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Clappana, India
- Bioclues.org, Hyderabad, India
| | - Harpreet Singh
- APBioNET.org, Singapore, Singapore
- Bioclues.org, Hyderabad, India
- Department of Bioinformatics, Hans Raj Mahila Maha Vidyalaya, Jalandhar, India
| | - Sarah L Morgan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Hilyatuz Zahroh
- APBioNET.org, Singapore, Singapore
- Genetics Research Centre, Universitas YARSI, Jakarta, Indonesia
| | - Maurice Ling
- APBioNET.org, Singapore, Singapore
- School of Applied Science, Temasek Polytechnic, Singapore, Singapore
| | - Venkata P Satagopam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
- International Society for Computational Biology, Leesburg, VA, USA
| | | | - Kenta Nakai
- Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Tin Wee Tan
- Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore, Singapore
- National Supercomputing Centre, Singapore, Singapore
| | - Ge Gao
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center and Beijing Advanced Innovation Center for Genomics, Center for Bioinformatics, Peking University, Beijing, China
| | - Nicola Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Christian Schönbach
- Department of Biology, School of Sciences and Humanities, Nazarbayev University, Astana, Kazakhstan
| | - Yun Zheng
- School of Landscape and Horticulture, Yunnan Agricultural University, Kunming, China
| | - Javier De Las Rivas
- Cancer Research Center, Spanish National Research Council, University of Salamanca & Institute for Biomedical Research of Salamanca, Salamanca, Spain
| | - Asif M Khan
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Istanbul, Turkey.
- APBioNET.org, Singapore, Singapore.
- Centre for Bioinformatics, School of Data Sciences, Perdana University, Kuala Lumpur, Malaysia.
- College of Computing and Information Technology, University of Doha for Science and Technology, Doha, Qatar.
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Ahmad S, Gromiha MM, Raghava GPS, Schönbach C, Ranganathan S. APBioNet's annual International Conference on Bioinformatics (InCoB) returns to India in 2018. BMC Genomics 2019; 19:266. [PMID: 30999857 PMCID: PMC7402400 DOI: 10.1186/s12864-019-5582-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
InCoB, one of the largest annual bioinformatics conferences in the Asia-Pacific region since its launch in 2002, returned to New Delhi, India after 12 years, with a conference attendance of 314 delegates. The 2018 conference had sessions on Big Data and Algorithms, Next Generation Sequencing and Omics Science, Structure, Function and Interactions, Disease and Drug Discovery and Plant and Agricultural Bioinformatics. The conference also featured an industry track as well as panel discussions on Women in Bioinformatics and Democratization vs. Quality control in academic publishing. Asia Pacific Bioinformatics Interaction & Networking Society (APbians) was launched as an APBionet Special Interest Group. Of the 52 oral presentations made, 22 were accepted in supplemental issues of BMC Bioinformatics, BMC Genomics or BMC Medical Genomics and are briefly reviewed here. Next year’s InCoB will be held in Jakarta, Indonesia from September 10–12, 2019.
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Affiliation(s)
- Shandar Ahmad
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110 067, India
| | - Michael M Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamilnadu, 600 036, India
| | - Gajendra P S Raghava
- Centre for Computational Biology, Indraprastha Institute of Information Technology, Okhla Industrial Estate, Phase III, New Delhi, 110020, India
| | - Christian Schönbach
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan.,International Research Center for Medical Sciences, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, 860-0811, Japan
| | - Shoba Ranganathan
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, 2109, Australia. .,Transformational Bioinformatics, Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Sydney, Australia.
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Yapiyev V, Gilman CP, Kabdullayeva T, Suleimenova A, Shagadatova A, Duisembay A, Naizabekov S, Mussurova S, Sydykova K, Raimkulov I, Kabimoldayev I, Abdrakhmanova A, Omarkulova S, Nurmukhambetov D, Kudarova A, Malgazhdar D, Schönbach C, Inglezakis V. Top soil physical and chemical properties in Kazakhstan across a north-south gradient. Sci Data 2018; 5:180242. [PMID: 30422127 PMCID: PMC6233482 DOI: 10.1038/sdata.2018.242] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Accepted: 09/10/2018] [Indexed: 11/09/2022] Open
Abstract
Kazakhstan’s soil properties have yet to be comprehensively characterized. We sampled 40 sites consisting of ten major soil types at spring (wet) and late-summer (dry) seasons. The sample locations range from semi-arid to arid with an annual mean air temperature from 1.2 to 10.7 °C and annual precipitation from less than 200 to around 400 mm. Overall topsoil total (STC), organic (SOC), and inorganic (SIC) carbon did not change significantly between spring and late summer. STC and SOC show a wave like pattern from north to south with two maxima in northern and southern Kazakhstan and one minimum in central Kazakhstan. With a few exceptions SIC content at northern sites is generally low, whereas at Lake Balkhash SIC can exceed 75% of STC. Independent of the seasons, SOC significantly differed among soil types. Total nitrogen content distribution among our sampling sites followed a similar pattern as SOC with significant differences between soil types occurring in northern, central and southern Kazakhstan.
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Affiliation(s)
- Vadim Yapiyev
- Department of Civil and Environmental Engineering, School of Engineering, Nazarbayev University, Astana, Kazakhstan.,National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan
| | - Charles P Gilman
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Tolganay Kabdullayeva
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Akmaral Suleimenova
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Aizhan Shagadatova
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Azat Duisembay
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Sanzhar Naizabekov
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Saule Mussurova
- National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan.,Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Kamilya Sydykova
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Ilyas Raimkulov
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Ilyas Kabimoldayev
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Ainagul Abdrakhmanova
- National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan.,Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
| | - Symbat Omarkulova
- Environmental Science & Technology Group (ESTg), Chemical Engineering Department, School of Engineering, Nazarbayev University, Astana, Kazakhstan
| | - Dastan Nurmukhambetov
- Environmental Science & Technology Group (ESTg), Chemical Engineering Department, School of Engineering, Nazarbayev University, Astana, Kazakhstan
| | - Aliya Kudarova
- Environmental Science & Technology Group (ESTg), Chemical Engineering Department, School of Engineering, Nazarbayev University, Astana, Kazakhstan
| | | | - Christian Schönbach
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, Kazakhstan.,International Research Center for Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Vassilis Inglezakis
- Environmental Science & Technology Group (ESTg), Chemical Engineering Department, School of Engineering, Nazarbayev University, Astana, Kazakhstan
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Schönbach C, Li J, Ma L, Horton P, Sjaugi MF, Ranganathan S. A bioinformatics potpourri. BMC Genomics 2018; 19:920. [PMID: 29363432 PMCID: PMC5780851 DOI: 10.1186/s12864-017-4326-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018.
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Affiliation(s)
- Christian Schönbach
- International Research Center for Medical Sciences, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, 860-0811 Japan
| | - Jinyan Li
- The Advanced Analytics Institute, University of Technology Sydney, Sydney, NSW 2007 Australia
| | - Lan Ma
- Graduate School at Shenzhen, Tsinghua University, Shenzhen, 518055 People’s Republic of China
| | - Paul Horton
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, 135-0064 Japan
| | | | - Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109 Australia
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Schönbach C, Verma C, Bond PJ, Ranganathan S. Bioinformatics and systems biology research update from the 15 th International Conference on Bioinformatics (InCoB2016). BMC Bioinformatics 2016; 17:524. [PMID: 28155668 PMCID: PMC5259976 DOI: 10.1186/s12859-016-1409-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The International Conference on Bioinformatics (InCoB) has been publishing peer-reviewed conference papers in BMC Bioinformatics since 2006. Of the 44 articles accepted for publication in supplement issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics and BMC Systems Biology, 24 articles with a bioinformatics or systems biology focus are reviewed in this editorial. InCoB2017 is scheduled to be held in Shenzen, China, September 20-22, 2017.
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Affiliation(s)
- Christian Schönbach
- International Research Center for Medical Sciences, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, 860-0811 Japan
| | - Chandra Verma
- Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, 138671 Singapore
| | - Peter J. Bond
- Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, 138671 Singapore
| | - Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109 Australia
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Abstract
InCoB became since its inception in 2002 one of the largest annual bioinformatics conferences in the Asia-Pacific region with attendance ranging between 150 and 250 delegates depending on the venue location. InCoB 2016 in Singapore was attended by almost 220 delegates. This year, sessions on structural bioinformatics, sequence and sequencing, and next-generation sequencing fielded the highest number of oral presentation. Forty-four out 96 oral presentations were associated with an accepted manuscript in supplemental issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics or BMC Systems Biology. Articles with a genomics focus are reviewed in this editorial. Next year's InCoB will be held in Shenzen, China from September 20 to 22, 2017.
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Affiliation(s)
- Christian Schönbach
- International Research Center for Medical Sciences, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, 860-0811 Japan
| | - Chandra Verma
- Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, 138671 Singapore
| | - Lawrence Jin Kiat Wee
- Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, 138632 Singapore
| | - Peter John Bond
- Bioinformatics Institute, Agency for Science, Technology and Research (A∗STAR), Singapore, 138671 Singapore
| | - Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109 Australia
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Sun X, Shi Y, Akahoshi T, Fujiwara M, Gatanaga H, Schönbach C, Kuse N, Appay V, Gao GF, Oka S, Takiguchi M. Effects of a Single Escape Mutation on T Cell and HIV-1 Co-adaptation. Cell Rep 2016; 15:2279-2291. [PMID: 27239036 DOI: 10.1016/j.celrep.2016.05.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Revised: 04/13/2016] [Accepted: 05/02/2016] [Indexed: 12/31/2022] Open
Abstract
The mechanistic basis for the progressive accumulation of Y(135)F Nef mutant viruses in the HIV-1-infected population remains poorly understood. Y(135)F viruses carry the 2F mutation within RW8 and RF10, which are two HLA-A(∗)24:02-restricted superimposed Nef epitopes recognized by distinct and adaptable CD8(+) T cell responses. We combined comprehensive analysis of the T cell receptor repertoire and cross-reactive potential of wild-type or 2F RW8- and RF10-specific CD8(+) T cells with peptide-MHC complex stability and crystal structure studies. We find that, by affecting direct and water-mediated hydrogen bond networks within the peptide-MHC complex, the 2F mutation reduces both TCR and HLA binding. This suggests an advantage underlying the evolution of the 2F variant with decreased CD8(+) T cell efficacy. Our study provides a refined understanding of HIV-1 and CD8(+) T cell co-adaptation at the population level.
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Affiliation(s)
- Xiaoming Sun
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan
| | - Yi Shi
- Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China
| | - Tomohiro Akahoshi
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan
| | - Mamoru Fujiwara
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan
| | - Hiroyuki Gatanaga
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan; AIDS Clinical Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan
| | - Christian Schönbach
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan; International Research Center of Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; Department of Biology, School of Science and Technology, Nazarbayev University, Astana 010000, Republic of Kazakhstan
| | - Nozomi Kuse
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan
| | - Victor Appay
- International Research Center of Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; INSERM, Unité Mixte de Recherche 1135, Sorbonne Universités, Université Pierre et Marie Curie, Université Paris 06, Centre d'Immunologie et des Maladies Infectieuses-Paris, 75013 Paris, France
| | - George F Gao
- Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China
| | - Shinichi Oka
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan; AIDS Clinical Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan
| | - Masafumi Takiguchi
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan; International Research Center of Medical Sciences (IRCMS), Kumamoto University, Kumamoto 860-0811, Japan; Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DS, UK.
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Schönbach C, Horton P, Yiu SM, Tan TW, Ranganathan S. GIW and InCoB, two premier bioinformatics conferences in Asia with a combined 40 years of history. BMC Genomics 2015; 16 Suppl 12:I1. [PMID: 26679412 PMCID: PMC4682400 DOI: 10.1186/1471-2164-16-s12-i1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Knowledge discovery in bioinformatics thrives on joint and inclusive efforts of stakeholders. Similarly, knowledge dissemination is expected to be more effective and scalable through joint efforts. Therefore, the International Conference on Bioinformatics (InCoB) and the International Conference on Genome Informatics (GIW) were organized as a joint conference for the first time in 13 years of coexistence. The Asia-Pacific Bioinformatics Network (APBioNet) and the Japanese Society for Bioinformatics (JSBi) collaborated to host GIW/InCoB2015 in Tokyo, September 9-11, 2015. The joint endeavour yielded 51 research articles published in seven journals, 78 poster and 89 oral presentations, showcasing bioinformatics research in the Asia-Pacific region. Encouraged by the results and reduced organizational overheads, APBioNet will collaborate with other bioinformatics societies in organizing co-located bioinformatics research and training meetings in the future. InCoB2016 will be hosted in Singapore, September 21-23, 2016.
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Schönbach C, Horton P, Yiu SM, Tan TW, Ranganathan S. GIW and InCoB are advancing bioinformatics in the Asia-Pacific. BMC Bioinformatics 2015; 16:I1. [PMID: 28102114 PMCID: PMC6389036 DOI: 10.1186/1471-2105-16-s18-i1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
GIW/InCoB2015 the joint 26th International Conference on Genome Informatics (GIW) and 14th International Conference on Bioinformatics (InCoB) held in Tokyo, September 9-11, 2015 was attended by over 200 delegates. Fifty-one out of 89 oral presentations were based on research articles accepted for publication in four BMC journal supplements and three other journals. Sixteen articles in this supplement and six articles in the BMC Systems Biology GIW/InCoB2015 Supplement are covered by this introduction. The topics range from genome informatics, protein structure informatics, image analysis to biological networks and biomarker discovery.
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Affiliation(s)
- Christian Schönbach
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana, 010000 Republic of Kazakhstan
- Center for AIDS Research and International Research Center for Medical Sciences, Kumamoto University, Kumamoto, 860-0811 Japan
| | - Paul Horton
- Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, 135-0064 Japan
- Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Japan
| | - Siu-Ming Yiu
- Department of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong, HKSAR
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117599
| | - Shoba Ranganathan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117599
- Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109 Australia
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Horton P, Schönbach C, Ranganathan S, Yiu SM. Introduction to selected papers from GIW/InCoB 2015. J Bioinform Comput Biol 2015; 13:1502003. [PMID: 26542445 DOI: 10.1142/s0219720015020035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Abstract
The 13th International Conference on Bioinformatics (InCoB2014) was held for the first time in Australia, at Sydney, July 31-2 August, 2014. InCoB is the annual scientific gathering of the Asia-Pacific Bioinformatics Network (APBioNet), hosted since 2002 in the Asia-Pacific region. Of 106 full papers submitted to the BMC track of InCoB2014, 50 (47.2%) were accepted in BMC Bioinformatics, BMC Genomics and BMC Systems Biology supplements, with three papers in a new BMC Medical Genomics supplement. While the majority of presenters and authors were from Asia and Australia, the increasing number of US and European conference attendees augurs well for the international flavour of InCoB. Next year's InCoB will be held jointly with the Genome Informatics Workshop (GIW), September 9-11, 2015 in Tokyo, Japan, with a view to integrate bioinformatics communities in the region.
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Ranganathan S, Tan TW, Schönbach C. InCoB2014: bioinformatics to tackle the data to knowledge challenge. Introduction. BMC Bioinformatics 2014; 15 Suppl 16:I1. [PMID: 25521055 PMCID: PMC4290632 DOI: 10.1186/1471-2105-15-s16-i1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Since 2006, the International Conference on Bioinformatics (InCoB) has been publishing selected papers in BMC Bioinformatics. Papers within the scope of the journal from the 13th InCoB July 31-2 August, 2014 in Sydney, Australia have been compiled in this supplement. These span protein and proteome informatics, structural bioinformatics, software development and bioimaging to pharmacoinformatics and disease informatics, representing the breadth of bioinformatics research in the Asia-Pacific.
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Affiliation(s)
- Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599
| | - Christian Schönbach
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana 010000, Republic of Kazakhstan
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan
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Ranganathan S, Tan TW, Schönbach C. InCoB2014: Systems Biology update from the Asia-Pacific. Introduction. BMC Syst Biol 2014; 8 Suppl 4:I1. [PMID: 25521591 PMCID: PMC4290681 DOI: 10.1186/1752-0509-8-s4-i1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Selected papers from the 13th International Conference on Bioinformatics (InCoB2014), July 31-2 August, 2014 in Sydney, Australia have been compiled in this supplement. These range from network analysis and gene regulatory networks to systems level biological analysis, providing the 2014 update to InCoB's computational systems biology research.
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Affiliation(s)
- Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599
| | - Christian Schönbach
- Department of Biology, School of Science and Technology, Nazarbayev University, Astana 010000, Republic of Kazakhstan
- Center for AIDS Research, Kumamoto University, Kumamoto 860-0811, Japan
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Abstract
The Asia-Pacific Bioinformatics Network (APBioNet) held the first International Conference on Bioinformatics (InCoB) in Bangkok in 2002 to promote North-South networking. Commencing as a forum for Asia-Pacific researchers to interact with and learn from with scientists of developed countries, InCoB has become a major regional bioinformatics conference, with participants from the region as well as North America and Europe. Since 2006, InCoB has selected the best submissions for publication in BMC Bioinformatics. In response to the growth and maturation of data-driven approaches, InCoB added BMC Genomics in 2009 and with the introduction of this conference supplement, BMC Systems Biology to its journal choices for submitting authors. Co-hosting InCoB2013 with the second International Conference for Translational Bioinformatics (ICTBI) is in line with InCoB's support for the current trend in taking bioinformatics to the bedside, along with a systems approach to solving biological problems.
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Affiliation(s)
- Asif M. Khan
- Perdana University Graduate School of Medicine, Selangor Darul Ehsan, Malaysia
- Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- * E-mail: (TWT); (SR)
| | - Christian Schönbach
- School of Science and Technology, Department of Biology and Chemistry, Nazarbayev University, Astana, Republic of Kazakhstan
- Department of Bioscience and Bioinformatics and Biomedical Informatics R&D Center (BMIRC), Kyushu Institute of Technology, Fukuoka, Japan
| | - Shoba Ranganathan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney, Australia
- * E-mail: (TWT); (SR)
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Olsen LR, Kudahl UJ, Simon C, Sun J, Schönbach C, Reinherz EL, Zhang GL, Brusic V. BlockLogo: visualization of peptide and sequence motif conservation. J Immunol Methods 2013; 400-401:37-44. [PMID: 24001880 DOI: 10.1016/j.jim.2013.08.014] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2013] [Revised: 08/20/2013] [Accepted: 08/25/2013] [Indexed: 12/21/2022]
Abstract
BlockLogo is a web-server application for the visualization of protein and nucleotide fragments, continuous protein sequence motifs, and discontinuous sequence motifs using calculation of block entropy from multiple sequence alignments. The user input consists of a multiple sequence alignment, selection of motif positions, type of sequence, and output format definition. The output has BlockLogo along with the sequence logo, and a table of motif frequencies. We deployed BlockLogo as an online application and have demonstrated its utility through examples that show visualization of T-cell epitopes and B-cell epitopes (both continuous and discontinuous). Our additional example shows a visualization and analysis of structural motifs that determine the specificity of peptide binding to HLA-DR molecules. The BlockLogo server also employs selected experimentally validated prediction algorithms to enable on-the-fly prediction of MHC binding affinity to 15 common HLA class I and class II alleles as well as visual analysis of discontinuous epitopes from multiple sequence alignments. It enables the visualization and analysis of structural and functional motifs that are usually described as regular expressions. It provides a compact view of discontinuous motifs composed of distant positions within biological sequences. BlockLogo is available at: http://research4.dfci.harvard.edu/cvc/blocklogo/ and http://met-hilab.bu.edu/blocklogo/.
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Affiliation(s)
- Lars Rønn Olsen
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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Abstract
Computational vaccinology or vaccine informatics is an interdisciplinary field that addresses scientific and clinical questions in vaccinology using computational and informatics approaches. Computational vaccinology overlaps with many other fields such as immunoinformatics, reverse vaccinology, postlicensure vaccine research, vaccinomics, literature mining, and systems vaccinology. The second ISV Pre-conference Computational Vaccinology Workshop (ICoVax 2012) was held on October 13, 2013 in Shanghai, China. A number of topics were presented in the workshop, including allergen predictions, prediction of linear T cell epitopes and functional conformational epitopes, prediction of protein-ligand binding regions, vaccine design using reverse vaccinology, and case studies in computational vaccinology. Although a significant progress has been made to date, a number of challenges still exist in the field. This Editorial provides a list of major challenges for the future of computational vaccinology and identifies developing themes that will expand and evolve over the next few years.
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Affiliation(s)
- Yongqun He
- Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, and Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Zhiwei Cao
- Department of Biomedical Engineering, College Life Science and Technology, Tongji University, Shanghai, 200092, China
| | - Anne S De Groot
- EpiVax, Inc., Providence, RI 02903, USA
- Institute for Immunology and Informatics, University of Rhode Island, Providence, RI 02903, USA
| | - Vladimir Brusic
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Christian Schönbach
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka 820-8502, Japan
- Biomedical Informatics Research and Development Center (BMIRC), Kyushu Institute of Technology, Fukuoka 820-8502, Japan
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Mizuno Y, Ninomiya Y, Nakachi Y, Iseki M, Iwasa H, Akita M, Tsukui T, Shimozawa N, Ito C, Toshimori K, Nishimukai M, Hara H, Maeba R, Okazaki T, Alodaib ANA, Amoudi MA, Jacob M, Alkuraya FS, Horai Y, Watanabe M, Motegi H, Wakana S, Noda T, Kurochkin IV, Mizuno Y, Schönbach C, Okazaki Y. Tysnd1 deficiency in mice interferes with the peroxisomal localization of PTS2 enzymes, causing lipid metabolic abnormalities and male infertility. PLoS Genet 2013; 9:e1003286. [PMID: 23459139 PMCID: PMC3573110 DOI: 10.1371/journal.pgen.1003286] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2012] [Accepted: 12/12/2012] [Indexed: 12/03/2022] Open
Abstract
Peroxisomes are subcellular organelles involved in lipid metabolic processes, including those of very-long-chain fatty acids and branched-chain fatty acids, among others. Peroxisome matrix proteins are synthesized in the cytoplasm. Targeting signals (PTS or peroxisomal targeting signal) at the C-terminus (PTS1) or N-terminus (PTS2) of peroxisomal matrix proteins mediate their import into the organelle. In the case of PTS2-containing proteins, the PTS2 signal is cleaved from the protein when transported into peroxisomes. The functional mechanism of PTS2 processing, however, is poorly understood. Previously we identified Tysnd1 (Trypsin domain containing 1) and biochemically characterized it as a peroxisomal cysteine endopeptidase that directly processes PTS2-containing prethiolase Acaa1 and PTS1-containing Acox1, Hsd17b4, and ScpX. The latter three enzymes are crucial components of the very-long-chain fatty acids β-oxidation pathway. To clarify the in vivo functions and physiological role of Tysnd1, we analyzed the phenotype of Tysnd1−/− mice. Male Tysnd1−/− mice are infertile, and the epididymal sperms lack the acrosomal cap. These phenotypic features are most likely the result of changes in the molecular species composition of choline and ethanolamine plasmalogens. Tysnd1−/− mice also developed liver dysfunctions when the phytanic acid precursor phytol was orally administered. Phyh and Agps are known PTS2-containing proteins, but were identified as novel Tysnd1 substrates. Loss of Tysnd1 interferes with the peroxisomal localization of Acaa1, Phyh, and Agps, which might cause the mild Zellweger syndrome spectrum-resembling phenotypes. Our data established that peroxisomal processing protease Tysnd1 is necessary to mediate the physiological functions of PTS2-containing substrates. Peroxisomes are subcellular organelles that are present in almost all eukaryotic cells. The syllables “per-oxi” reflect the oxidative functions of these single-membrane-bound organelles in various metabolic processes, including those of very-long-chain fatty acids and branched-chain fatty acids. In an earlier study we identified a protease named Tysnd1 that is specifically located in the peroxisomes and processes the enzymes catalyzing the peroxisomal β-oxidation of very-long-chain fatty acids. In this study, we identified two novel Tysnd1 substrates, Agps and Phyh, which are involved in plasmalogen synthesis and phytanic acid metabolism, respectively. To further investigate the in vivo function of Tysnd1, we analyzed Tysnd1 knock-out mice. Mice that lack Tysnd1 showed reduced peroxisomal β-oxidation activity and an altered plasmalogen composition, as well as an abnormal phytanic acid metabolism. Male infertility is one of the major phenotypic manifestations of Tysnd1 deficiency. Our data support the idea that Tysnd1 affects the localization and activity of some of its substrates inside peroxisomes. Altogether, our Tysnd1-deficient mouse model expands the current peroxisome biology knowledge with regard to the molecular pathogenic mechanisms that may be relevant to some patients with Zellweger syndrome spectrum disorders.
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Affiliation(s)
- Yumi Mizuno
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
- Division of Translational Research, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Yuichi Ninomiya
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Yutaka Nakachi
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
- Division of Translational Research, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Mioko Iseki
- Division of Translational Research, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Hiroyasu Iwasa
- Division of Translational Research, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Masumi Akita
- Division of Morphological Science, Biomedical Research Center, Saitama Medical University, Iruma-gun, Saitama, Japan
| | - Tohru Tsukui
- Experimental Animal Laboratory, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Nobuyuki Shimozawa
- Division of Genomics Research, Life Science Research Center, Gifu University, Gifu, Japan
| | - Chizuru Ito
- Department of Anatomy and Developmental Biology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Kiyotaka Toshimori
- Department of Anatomy and Developmental Biology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Megumi Nishimukai
- Laboratory of Nutritional Biochemistry, Research Group of Food Science, Division of Applied Bioscience, Graduate School of Agriculture, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Hiroshi Hara
- Laboratory of Nutritional Biochemistry, Research Group of Food Science, Division of Applied Bioscience, Graduate School of Agriculture, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Ryouta Maeba
- Department of Biochemistry, Teikyo University School of Medicine, Itabashi-ku, Tokyo, Japan
| | - Tomoki Okazaki
- Department of Biochemistry, Teikyo University School of Medicine, Itabashi-ku, Tokyo, Japan
| | - Ali Nasser Ali Alodaib
- Developmental Genetics Department, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
- The National Newborn Screening Laboratory, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Mohammed Al Amoudi
- Developmental Genetics Department, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
- The National Newborn Screening Laboratory, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Minnie Jacob
- Developmental Genetics Department, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
- The National Newborn Screening Laboratory, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Fowzan S. Alkuraya
- Developmental Genetics Department, Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia
- Department of Pediatrics, King Khalid University Hospital and College of Medicine, King Saud University, Riyadh, Kingdom of Saudi Arabia
- Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, Riyadh, Kingdom of Saudi Arabia
| | - Yasushi Horai
- Department of Internal Medicine, School of Medicine, Keio University, Shinjuku-ku, Tokyo, Japan
| | - Mitsuhiro Watanabe
- Department of Internal Medicine, School of Medicine, Keio University, Shinjuku-ku, Tokyo, Japan
- Graduate School of Media and Governance, Keio University, Tokyo, Japan
- Faculty of Environment and Information Studies, Keio University, Tokyo, Japan
| | - Hiromi Motegi
- Team for Advanced Development and Evaluation of Human Disease Models, Japan Mouse Clinic, BioResource Center (BRC), Tsukuba, Ibaraki, Japan
| | - Shigeharu Wakana
- The Japan Mouse Clinic, RIKEN BioResource Center (BRC), Tsukuba, Ibaraki, Japan
| | - Tetsuo Noda
- Team for Advanced Development and Evaluation of Human Disease Models, Japan Mouse Clinic, BioResource Center (BRC), Tsukuba, Ibaraki, Japan
- The Cancer Institute of the Japanese Foundation for Cancer Research, Koto-ku, Tokyo, Japan
| | - Igor V. Kurochkin
- Genome and Gene Expression Data Analysis Division, Bioinformatics Institute, A*STAR, Singapore, Republic of Singapore
| | - Yosuke Mizuno
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | - Christian Schönbach
- Division of Genomics and Genetics, School of Biological Sciences, Nanyang Technological University, Singapore, Republic of Singapore
| | - Yasushi Okazaki
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
- Division of Translational Research, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
- * E-mail:
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Su CTT, Schönbach C, Kwoh CK. Molecular docking analysis of 2009-H1N1 and 2004-H5N1 influenza virus HLA-B*4405-restricted HA epitope candidates: implications for TCR cross-recognition and vaccine development. BMC Bioinformatics 2013; 14 Suppl 2:S21. [PMID: 23368875 PMCID: PMC3549837 DOI: 10.1186/1471-2105-14-s2-s21] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Background The pandemic 2009-H1N1 influenza virus circulated in the human population and caused thousands deaths worldwide. Studies on pandemic influenza vaccines have shown that T cell recognition to conserved epitopes and cross-reactive T cell responses are important when new strains emerge, especially in the absence of antibody cross-reactivity. In this work, using HLA-B*4405 and DM1-TCR structure model, we systematically generated high confidence conserved 2009-H1N1 T cell epitope candidates and investigated their potential cross-reactivity against H5N1 avian flu virus. Results Molecular docking analysis of differential DM1-TCR recognition of the 2009-H1N1 epitope candidates yielded a mosaic epitope (KEKMNTEFW) and potential H5N1 HA cross-reactive epitopes that could be applied as multivalent peptide towards influenza A vaccine development. Structural models of TCR cross-recognition between 2009-H1N1 and 2004-H5N1 revealed steric and topological effects of TCR contact residue mutations on TCR binding affinity. Conclusions The results are novel with regard to HA epitopes and useful for developing possible vaccination strategies against the rapidly changing influenza viruses. Yet, the challenge of identifying epitope candidates that result in heterologous T cell immunity under natural influenza infection conditions can only be overcome if more structural data on the TCR repertoire become available.
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Affiliation(s)
- Chinh T T Su
- Bioinformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore
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Ranganathan S, Tongsima S, Chan J, Tan TW, Schönbach C. Advances in translational bioinformatics and population genomics in the Asia-Pacific. BMC Genomics 2013; 13 Suppl 7:S1. [PMID: 23282089 PMCID: PMC3521394 DOI: 10.1186/1471-2164-13-s7-s1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
The theme of the 2012 International Conference on Bioinformatics (InCoB) in Bangkok, Thailand was "From Biological Data to Knowledge to Technological Breakthroughs." Besides providing a forum for life scientists and bioinformatics researchers in the Asia-Pacific region to meet and interact, the conference also hosted thematic sessions on the Pan-Asian Pacific Genome Initiative and immunoinformatics. Over the seven years of conference papers published in BMC Bioinformatics and four years in BMC Genomics, we note that there is increasing interest in the applications of -omics technologies to the understanding of diseases, as a forerunner to personalized genomic medicine.
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Affiliation(s)
- Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence, Macquarie University, Sydney, NSW 2109, Australia
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Schönbach C, Tongsima S, Chan J, Brusic V, Tan TW, Ranagathan S. InCoB2012 Conference: from biological data to knowledge to technological breakthroughs. BMC Bioinformatics 2012; 13 Suppl 17:S1. [PMID: 23281929 PMCID: PMC3521245 DOI: 10.1186/1471-2105-13-s17-s1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Ten years ago when Asia-Pacific Bioinformatics Network held the first International Conference on Bioinformatics (InCoB) in Bangkok its theme was North-South Networking. At that time InCoB aimed to provide biologists and bioinformatics researchers in the Asia-Pacific region a forum to meet, interact with, and disseminate knowledge about the burgeoning field of bioinformatics. Meanwhile InCoB has evolved into a major regional bioinformatics conference that attracts not only talented and established scientists from the region but increasingly also from East Asia, North America and Europe. Since 2006 InCoB yielded 114 articles in BMC Bioinformatics supplement issues that have been cited nearly 1,000 times to date. In part, these developments reflect the success of bioinformatics education and continuous efforts to integrate and utilize bioinformatics in biotechnology and biosciences in the Asia-Pacific region. A cross-section of research leading from biological data to knowledge and to technological applications, the InCoB2012 theme, is introduced in this editorial. Other highlights included sessions organized by the Pan-Asian Pacific Genome Initiative and a Machine Learning in Immunology competition. InCoB2013 is scheduled for September 18-21, 2013 at Suzhou, China.
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Affiliation(s)
- Christian Schönbach
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka 820-8502, Japan
- Biomedical Informatics Research and Development Center, Kyushu Institute of Technology, Fukuoka 820-8502, Japan
| | - Sissades Tongsima
- National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathumthani 12120, Thailand
| | - Jonathan Chan
- School of Information Technology, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Vladimir Brusic
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Republic of Singapore
- Computational Resource Centre (A*CRC), A*STAR, Singapore 138632, Republic of Singapore
| | - Shoba Ranagathan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Republic of Singapore
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence, Macquarie University, Sydney, NSW 2109, Australia
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Schönbach C, Tan TW, Kelso J, Rost B, Nathan S, Ranganathan S. InCoB celebrates its tenth anniversary as first joint conference with ISCB-Asia. BMC Genomics 2011; 12 Suppl 3:S1. [PMID: 22369160 PMCID: PMC3333168 DOI: 10.1186/1471-2164-12-s3-s1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
In 2009 the International Society for Computational Biology (ISCB) started to roll out regional bioinformatics conferences in Africa, Latin America and Asia. The open and competitive bid for the first meeting in Asia (ISCB-Asia) was awarded to Asia-Pacific Bioinformatics Network (APBioNet) which has been running the International Conference on Bioinformatics (InCoB) in the Asia-Pacific region since 2002. InCoB/ISCB-Asia 2011 is held from November 30 to December 2, 2011 in Kuala Lumpur, Malaysia. Of 104 manuscripts submitted to BMC Genomics and BMC Bioinformatics conference supplements, 49 (47.1%) were accepted. The strong showing of Asia among submissions (82.7%) and acceptances (81.6%) signals the success of this tenth InCoB anniversary meeting, and bodes well for the future of ISCB-Asia.
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Affiliation(s)
- Christian Schönbach
- Department of Bioscience and Bioinformatics, Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka 820-8502, Japan.
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Ranganathan S, Schönbach C, Kelso J, Rost B, Nathan S, Tan TW. Towards big data science in the decade ahead from ten years of InCoB and the 1st ISCB-Asia Joint Conference. BMC Bioinformatics 2011; 12 Suppl 13:S1. [PMID: 22372736 PMCID: PMC3278825 DOI: 10.1186/1471-2105-12-s13-s1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
The 2011 International Conference on Bioinformatics (InCoB) conference, which is the annual scientific conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted by Kuala Lumpur, Malaysia, is co-organized with the first ISCB-Asia conference of the International Society for Computational Biology (ISCB). InCoB and the sequencing of the human genome are both celebrating their tenth anniversaries and InCoB’s goalposts for the next decade, implementing standards in bioinformatics and globally distributed computational networks, will be discussed and adopted at this conference. Of the 49 manuscripts (selected from 104 submissions) accepted to BMC Genomics and BMC Bioinformatics conference supplements, 24 are featured in this issue, covering software tools, genome/proteome analysis, systems biology (networks, pathways, bioimaging) and drug discovery and design.
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Affiliation(s)
- Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia.
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24
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Ranganathan S, Schönbach C, Nakai K, Tan TW. Challenges of the next decade for the Asia Pacific region: 2010 International Conference in Bioinformatics (InCoB 2010). BMC Genomics 2010; 11 Suppl 4:S1. [PMID: 21143792 PMCID: PMC3005919 DOI: 10.1186/1471-2164-11-s4-s1] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The 2010 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia’s oldest bioinformatics organisation formed in 1998, was organized as the 9th International Conference on Bioinformatics (InCoB), Sept. 26-28, 2010 in Tokyo, Japan. Initially, APBioNet created InCoB as forum to foster bioinformatics in the Asia Pacific region. Given the growing importance of interdisciplinary research, InCoB2010 included topics targeting scientists in the fields of genomic medicine, immunology and chemoinformatics, supporting translational research. Peer-reviewed manuscripts that were accepted for publication in this supplement, represent key areas of research interests that have emerged in our region. We also highlight some of the current challenges bioinformatics is facing in the Asia Pacific region and conclude our report with the announcement of APBioNet’s 100 BioDatabases (BioDB100) initiative. BioDB100 will comply with the database criteria set out earlier in our proposal for Minimum Information about a Bioinformatics and Investigation (MIABi), setting the standards for biocuration and bioinformatics research, on which we will report at the next InCoB, Nov. 27 – Dec. 2, 2011 at Kuala Lumpur, Malaysia.
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Affiliation(s)
- Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW, Australia.
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25
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Abstract
The International Conference on Bioinformatics (InCoB), the annual conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted in one of countries of the Asia-Pacific region. The 2010 conference was awarded to Japan and has attracted more than one hundred high-quality research paper submissions. Thorough peer reviewing resulted in 47 (43.5%) accepted papers out of 108 submissions. Submissions from Japan, R.O. Korea, P.R. China, Australia, Singapore and U.S.A totaled 43.8% and contributed to 57.4% of accepted papers. Manuscripts originating from Taiwan and India added up to 42.8% of submissions and 28.3% of acceptances. The fifteen articles published in this BMC Bioinformatics supplement cover disease informatics, structural bioinformatics and drug design, biological databases and software tools, signaling pathways, gene regulatory and biochemical networks, evolution and sequence analysis.
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Affiliation(s)
- Christian Schönbach
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka 820-8502, Japan
| | - Kenta Nakai
- Laboratory of Functional Analysis in silico, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597
| | - Shoba Ranganathan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597
- Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia
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Tokuzawa Y, Yagi K, Yamashita Y, Nakachi Y, Nikaido I, Bono H, Ninomiya Y, Kanesaki-Yatsuka Y, Akita M, Motegi H, Wakana S, Noda T, Sablitzky F, Arai S, Kurokawa R, Fukuda T, Katagiri T, Schönbach C, Suda T, Mizuno Y, Okazaki Y. Id4, a new candidate gene for senile osteoporosis, acts as a molecular switch promoting osteoblast differentiation. PLoS Genet 2010; 6:e1001019. [PMID: 20628571 PMCID: PMC2900302 DOI: 10.1371/journal.pgen.1001019] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2010] [Accepted: 06/04/2010] [Indexed: 01/03/2023] Open
Abstract
Excessive accumulation of bone marrow adipocytes observed in senile osteoporosis or age-related osteopenia is caused by the unbalanced differentiation of MSCs into bone marrow adipocytes or osteoblasts. Several transcription factors are known to regulate the balance between adipocyte and osteoblast differentiation. However, the molecular mechanisms that regulate the balance between adipocyte and osteoblast differentiation in the bone marrow have yet to be elucidated. To identify candidate genes associated with senile osteoporosis, we performed genome-wide expression analyses of differentiating osteoblasts and adipocytes. Among transcription factors that were enriched in the early phase of differentiation, Id4 was identified as a key molecule affecting the differentiation of both cell types. Experiments using bone marrow-derived stromal cell line ST2 and Id4-deficient mice showed that lack of Id4 drastically reduces osteoblast differentiation and drives differentiation toward adipocytes. On the other hand knockdown of Id4 in adipogenic-induced ST2 cells increased the expression of Pparγ2, a master regulator of adipocyte differentiation. Similar results were observed in bone marrow cells of femur and tibia of Id4-deficient mice. However the effect of Id4 on Pparγ2 and adipocyte differentiation is unlikely to be of direct nature. The mechanism of Id4 promoting osteoblast differentiation is associated with the Id4-mediated release of Hes1 from Hes1-Hey2 complexes. Hes1 increases the stability and transcriptional activity of Runx2, a key molecule of osteoblast differentiation, which results in an enhanced osteoblast-specific gene expression. The new role of Id4 in promoting osteoblast differentiation renders it a target for preventing the onset of senile osteoporosis. Increased bone marrow adiposity is observed in the bone marrow of senile osteoporosis patients. This is caused by unbalanced differentiation of mesenchymal stem cells (MSCs) into osteoblast or adipocyte. Previous reports have indicated that several transcription factors play important roles in determining the direction of MSCs differentiation into osteoblast or adipocyte. So far, little is known about the overall dynamics and regulation of transcription factor expression changes leading to the imbalance of osteoblast and adipocyte differentiation inside the bone marrow. We have performed genome-wide gene expression analyses during the differentiation of MSCs into osteoblast or adipocyte. We identified basic helix-loop-helix transcription factor family member Id4 as a leading candidate controlling the differentiation toward adipocyte or osteoblast. Suppression of Id4 expression in MSCs repressed osteoblast differentiation and increased adipocyte differentiation. In contrast, overexpression of Id4 in MSCs promoted osteoblast differentiation and attenuated adipocyte differentiation. Moreover, Id4-mutant mice showed abnormal accumulation of lipid droplets in bone marrow and impaired bone formation activity. In summary, we have demonstrated a molecular function of Id4 in osteoblast differentiation. The findings revealed that Id4 is a molecular switch enhancing osteoblast differentiation at the expense of adipocyte differentiation.
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Affiliation(s)
- Yoshimi Tokuzawa
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Ken Yagi
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Yzumi Yamashita
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Yutaka Nakachi
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Itoshi Nikaido
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Hidemasa Bono
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Yuichi Ninomiya
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Yukiko Kanesaki-Yatsuka
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Masumi Akita
- Division of Morphological Science, Biomedical Research Center, Saitama Medical University, Iruma-gun, Saitama, Japan
| | | | | | - Tetsuo Noda
- RIKEN BioResource Center, Tsukuba, Ibaraki, Japan
- The Cancer Institute of the Japanese Foundation for Cancer Research, Koto-ward, Tokyo, Japan
| | - Fred Sablitzky
- Developmental Genetics and Gene Control, Institute of Genetics, University of Nottingham, Queen's Medical Center, Nottingham, United Kingdom
| | - Shigeki Arai
- Division of Gene Structure and Function, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Riki Kurokawa
- Division of Gene Structure and Function, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Toru Fukuda
- Division of Pathophysiology, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Takenobu Katagiri
- Division of Pathophysiology, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Christian Schönbach
- Division of Genomics and Genetics, Nanyang Technological University School of Biological Sciences, Singapore, Singapore
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan
| | - Tatsuo Suda
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Yosuke Mizuno
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
| | - Yasushi Okazaki
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan
- * E-mail:
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Mizuno Y, Kurochkin IV, Herberth M, Okazaki Y, Schönbach C. Predicted mouse peroxisome-targeted proteins and their actual subcellular locations. BMC Bioinformatics 2008; 9 Suppl 12:S16. [PMID: 19091015 PMCID: PMC2638156 DOI: 10.1186/1471-2105-9-s12-s16] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The import of most intraperoxisomal proteins is mediated by peroxisome targeting signals at their C-termini (PTS1) or N-terminal regions (PTS2). Both signals have been integrated in subcellular location prediction programs. However their present performance, particularly of PTS2-targeting did not seem fitting for large-scale screening of sequences. RESULTS We modified an earlier reported PTS1 screening method to identify PTS2-containing mouse candidates using a combination of computational and manual annotation. For rapid confirmation of five new PTS2- and two previously identified PTS1-containing candidates we developed the new cell line CHO-perRed which stably expresses the peroxisomal marker dsRed-PTS1. Using CHO-perRed we confirmed the peroxisomal localization of PTS1-targeted candidate Zadh2. Preliminary characterization of Zadh2 expression suggested non-PPARalpha mediated activation. Notably, none of the PTS2 candidates located to peroxisomes. CONCLUSION In a few cases the PTS may oscillate from "silent" to "functional" depending on its surface accessibility indicating the potential for context-dependent conditional subcellular sorting. Overall, PTS2-targeting predictions are unlikely to improve without generation and integration of new experimental data from location proteomics, protein structures and quantitative Pex7 PTS2 peptide binding assays.
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Affiliation(s)
- Yumi Mizuno
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama 350-1241, Japan.
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Schönbach C. The RIKEN mouse transcriptome: lessons learned and implications for the regulation of immune reactions. Novartis Found Symp 2007; 281:25-34; discussion 34-7, 50-3, 208-9. [PMID: 17534063 DOI: 10.1002/9780470062128.ch3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Notably, the technology and analysis methods of the RIKEN mouse full-length cDNA project have contributed a lot to the capture of the transcriptional output of the mouse genome and the description of its combinatorial nature. However, one corollary of this large scale transcript resource is the dichotomy of vast and missing information. As such, the transcriptional and translational output of yet unknown size following non-canonical principles remains to be established and interpreted. The importance of identifying immune-related transcripts and establishing their molecular functions in context of complex immune system diseases is clear: knowledge about the transcriptome can advance the understanding of immune system regulation. Decipher ing the logic of transcriptomes is critical for understanding the ontogeny and effector functions of immune cells, but it is not sufficient. The next challenge will lie in the combined sampling and integrated analysis of genomic elements, transcripts, proteins and metabolites.
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Affiliation(s)
- Christian Schönbach
- Immunoinformatics Research Team, Advanced Genome Information Technology Group, RIKEN Genomic Sciences Center (GSC), 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan
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Kurochkin IV, Mizuno Y, Konagaya A, Sakaki Y, Schönbach C, Okazaki Y. Novel peroxisomal protease Tysnd1 processes PTS1- and PTS2-containing enzymes involved in beta-oxidation of fatty acids. EMBO J 2007; 26:835-45. [PMID: 17255948 PMCID: PMC1794383 DOI: 10.1038/sj.emboj.7601525] [Citation(s) in RCA: 76] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2006] [Accepted: 12/05/2006] [Indexed: 12/21/2022] Open
Abstract
Peroxisomes play an important role in beta-oxidation of fatty acids. All peroxisomal matrix proteins are synthesized in the cytosol and post-translationally sorted to the organelle. Two distinct peroxisomal signal targeting sequences (PTSs), the C-terminal PTS1 and the N-terminal PTS2, have been defined. Import of precursor PTS2 proteins into the peroxisomes is accompanied by a proteolytic removal of the N-terminal targeting sequence. Although the PTS1 signal is preserved upon translocation, many PTS1 proteins undergo a highly selective and limited cleavage. Here, we demonstrate that Tysnd1, a previously uncharacterized protein, is responsible both for the removal of the leader peptide from PTS2 proteins and for the specific processing of PTS1 proteins. All of the identified Tysnd1 substrates catalyze peroxisomal beta-oxidation. Tysnd1 itself undergoes processing through the removal of the presumably inhibitory N-terminal fragment. Tysnd1 expression is induced by the proliferator-activated receptor alpha agonist bezafibrate, along with the increase in its substrates. A model is proposed where the Tysnd1-mediated processing of the peroxisomal enzymes promotes their assembly into a supramolecular complex to enhance the rate of beta-oxidation.
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Affiliation(s)
- Igor V Kurochkin
- Immunoinformatics Team, Advanced Genome Information Group, RIKEN Genomic Sciences Center, Yokohama, Japan
- Present address: Genome Annotation and Comparative Analysis Team, Computational and Experimental Systems Biology Group, RIKEN Genomic Sciences Center, Yokohama 230-0045, Japan
- IV Kurochkin, Genome Annotation and Comparative Analysis Team, Computational and Experimental Systems Biology Group, RIKEN Genomic Sciences Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan. Tel.: +81 45 503 9111 (ext 8106); Fax: +81 45 503 9176; E-mail:
| | - Yumi Mizuno
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
| | | | - Yoshiyuki Sakaki
- Computational and Experimental Systems Biology Group, RIKEN Genomic Sciences Center, Yokohama, Japan
| | - Christian Schönbach
- Immunoinformatics Team, Advanced Genome Information Group, RIKEN Genomic Sciences Center, Yokohama, Japan
| | - Yasushi Okazaki
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka-shi, Saitama, Japan
- Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, 1397-1 Yamane, Hidaka-city, Saitama 350-1241, Japan. Tel.: +81 42 985 7319; Fax: +81 42 985 7329; E-mail:
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Brahmachary M, Schönbach C, Yang L, Huang E, Tan SL, Chowdhary R, Krishnan SPT, Lin CY, Hume DA, Kai C, Kawai J, Carninci P, Hayashizaki Y, Bajic VB. Computational promoter analysis of mouse, rat and human antimicrobial peptide-coding genes. BMC Bioinformatics 2006; 7 Suppl 5:S8. [PMID: 17254313 PMCID: PMC1764486 DOI: 10.1186/1471-2105-7-s5-s8] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mammalian antimicrobial peptides (AMPs) are effectors of the innate immune response. A multitude of signals coming from pathways of mammalian pathogen/pattern recognition receptors and other proteins affect the expression of AMP-coding genes (AMPcgs). For many AMPcgs the promoter elements and transcription factors that control their tissue cell-specific expression have yet to be fully identified and characterized. RESULTS Based upon the RIKEN full-length cDNA and public sequence data derived from human, mouse and rat, we identified 178 candidate AMP transcripts derived from 61 genes belonging to 29 AMP families. However, only for 31 mouse genes belonging to 22 AMP families we were able to determine true orthologous relationships with 30 human and 15 rat sequences. We screened the promoter regions of AMPcgs in the three species for motifs by an ab initio motif finding method and analyzed the derived promoter characteristics. Promoter models were developed for alpha-defensins, penk and zap AMP families. The results suggest a core set of transcription factors (TFs) that regulate the transcription of AMPcg families in mouse, rat and human. The three most frequent core TFs groups include liver-, nervous system-specific and nuclear hormone receptors (NHRs). Out of 440 motifs analyzed, we found that three represent potentially novel TF-binding motifs enriched in promoters of AMPcgs, while the other four motifs appear to be species-specific. CONCLUSION Our large-scale computational analysis of promoters of 22 families of AMPcgs across three mammalian species suggests that their key transcriptional regulators are likely to be TFs of the liver-, nervous system-specific and NHR groups. The computationally inferred promoter elements and potential TF binding motifs provide a rich resource for targeted experimental validation of TF binding and signaling studies that aim at the regulation of mouse, rat or human AMPcgs.
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Affiliation(s)
- Manisha Brahmachary
- Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
- Department of Biochemistry, Faculty of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
| | - Christian Schönbach
- Immunoinformatics Research Team, Advanced Genome Information Technology Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
- Division of Genomics and Genetics, School of Biological Sciences, Nanyang Technological University, Singapore 637551, Singapore
| | - Liang Yang
- Department of Obstetrics and Gynecology, National University Hospital, National University of Singapore, 5 Lower Kent Ridge Road, Singapore 119074, Singapore
| | - Enli Huang
- Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
| | - Sin Lam Tan
- Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
- University of the Western Cape, South African National Bioinformatics Institute (SANBI), Private Bag X17, Bellville 7535, South Africa
| | - Rajesh Chowdhary
- Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
| | - SPT Krishnan
- Knowledge Extraction Laboratory, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
| | - Chin-Yo Lin
- Brigham Young University, Department of Microbiology and Molecular Biology, 753 WIDB, Provo, UT 84602, USA
| | - David A Hume
- ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Chikatoshi Kai
- Genome Exploration Research Group (Genome Network Project Core Group), RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Jun Kawai
- Genome Exploration Research Group (Genome Network Project Core Group), RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
- Genome Science Laboratory, Discovery Research Institute, RIKEN Wako Institute, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
| | - Piero Carninci
- Genome Exploration Research Group (Genome Network Project Core Group), RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
- Genome Science Laboratory, Discovery Research Institute, RIKEN Wako Institute, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
| | - Yoshihide Hayashizaki
- Genome Exploration Research Group (Genome Network Project Core Group), RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
- Genome Science Laboratory, Discovery Research Institute, RIKEN Wako Institute, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
| | - Vladimir B Bajic
- University of the Western Cape, South African National Bioinformatics Institute (SANBI), Private Bag X17, Bellville 7535, South Africa
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Bajic VB, Tan SL, Christoffels A, Schönbach C, Lipovich L, Yang L, Hofmann O, Kruger A, Hide W, Kai C, Kawai J, Hume DA, Carninci P, Hayashizaki Y. Mice and men: their promoter properties. PLoS Genet 2006; 2:e54. [PMID: 16683032 PMCID: PMC1449896 DOI: 10.1371/journal.pgen.0020054] [Citation(s) in RCA: 84] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2005] [Accepted: 02/27/2006] [Indexed: 12/28/2022] Open
Abstract
Using the two largest collections of Mus musculus and Homo sapiens transcription start sites (TSSs) determined based on CAGE tags, ditags, full-length cDNAs, and other transcript data, we describe the compositional landscape surrounding TSSs with the aim of gaining better insight into the properties of mammalian promoters. We classified TSSs into four types based on compositional properties of regions immediately surrounding them. These properties highlighted distinctive features in the extended core promoters that helped us delineate boundaries of the transcription initiation domain space for both species. The TSS types were analyzed for associations with initiating dinucleotides, CpG islands, TATA boxes, and an extensive collection of statistically significant cis-elements in mouse and human. We found that different TSS types show preferences for different sets of initiating dinucleotides and cis-elements. Through Gene Ontology and eVOC categories and tissue expression libraries we linked TSS characteristics to expression. Moreover, we show a link of TSS characteristics to very specific genomic organization in an example of immune-response-related genes (GO:0006955). Our results shed light on the global properties of the two transcriptomes not revealed before and therefore provide the framework for better understanding of the transcriptional mechanisms in the two species, as well as a framework for development of new and more efficient promoter- and gene-finding tools.
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Affiliation(s)
- Vladimir B Bajic
- Knowledge Extraction Laboratory, Institute for Infocomm Research, Singapore.
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Abstract
BACKGROUND Peroxisomes are metabolic organelles present in virtually all eukaryotic cells. They contain enzymes involved in hydrogen peroxide-based respiration and lipid metabolism. At present, only a small number of peroxisomal enzymes that are associated with oxidative stress response and metabolic disorders have been characterised biochemically. Therefore, we devised a sequence-based, multistep knowledge discovery strategy to identify potential novel peroxisomal protein candidates in small rodent model organisms and human. METHODS Screening of 130,629 putative translations of GenBank rodent and primate mRNA sequences was limited to the classical type-1 peroxisomal targeting signal [SA]-K-L. This motif is over-represented among peroxisomal proteins and has a high targeting efficiency. Subsequent steps of identifying co-occurring motifs, secondary structure properties, orthologues and variants, in combination with literature searching and visual inspection by domain experts, aimed at reduction of both false positive and negative validation targets. RESULTS Our method yielded 117 known peroxisome-targeted proteins and 29 novel candidate proteins. Of special interest were the mouse C530046K17Rik and 1300019N10Rik protein sequences that contain domains associated with enzymatic functions. C530046K17Rik showed no similarity to any known sequence of the animal kingdom, but weak similarity to the possible Leishmania quinone oxidoreductase and a putative cyanobacterium nicotinamide adenine dinucleotide phosphate (NADP)-dependent oxidoreductase. 1300019N10Rik contains two protease-related domains, glutamyl endopeptidase I and trypsin-like serine and cysteine proteases, which may have unique specificities to achieve efficient breakdown of proteins in the peroxisomes. CONCLUSION One mouse C57BL/6J strain-specific isocitrate dehydrogenase 1 isoform might be suitable to investigate potential phenotypes associated with the deficit of the intraperoxisomal reduced form of NADP (NADPH) and 2-oxoglutarate. Our biological knowledge discovery strategy enabled not only the identification of peroxisomal enzymes already described in the literature, but also the prediction of several novel proteins with possible roles in peroxisomal biochemistry and metabolism that are currently under experimental validation.
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Affiliation(s)
- Igor V Kurochkin
- Immunoinformatics Team, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Yokohama, Japan
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Carninci P, Kasukawa T, Katayama S, Gough J, Frith MC, Maeda N, Oyama R, Ravasi T, Lenhard B, Wells C, Kodzius R, Shimokawa K, Bajic VB, Brenner SE, Batalov S, Forrest ARR, Zavolan M, Davis MJ, Wilming LG, Aidinis V, Allen JE, Ambesi-Impiombato A, Apweiler R, Aturaliya RN, Bailey TL, Bansal M, Baxter L, Beisel KW, Bersano T, Bono H, Chalk AM, Chiu KP, Choudhary V, Christoffels A, Clutterbuck DR, Crowe ML, Dalla E, Dalrymple BP, de Bono B, Della Gatta G, di Bernardo D, Down T, Engstrom P, Fagiolini M, Faulkner G, Fletcher CF, Fukushima T, Furuno M, Futaki S, Gariboldi M, Georgii-Hemming P, Gingeras TR, Gojobori T, Green RE, Gustincich S, Harbers M, Hayashi Y, Hensch TK, Hirokawa N, Hill D, Huminiecki L, Iacono M, Ikeo K, Iwama A, Ishikawa T, Jakt M, Kanapin A, Katoh M, Kawasawa Y, Kelso J, Kitamura H, Kitano H, Kollias G, Krishnan SPT, Kruger A, Kummerfeld SK, Kurochkin IV, Lareau LF, Lazarevic D, Lipovich L, Liu J, Liuni S, McWilliam S, Madan Babu M, Madera M, Marchionni L, Matsuda H, Matsuzawa S, Miki H, Mignone F, Miyake S, Morris K, Mottagui-Tabar S, Mulder N, Nakano N, Nakauchi H, Ng P, Nilsson R, Nishiguchi S, Nishikawa S, Nori F, Ohara O, Okazaki Y, Orlando V, Pang KC, Pavan WJ, Pavesi G, Pesole G, Petrovsky N, Piazza S, Reed J, Reid JF, Ring BZ, Ringwald M, Rost B, Ruan Y, Salzberg SL, Sandelin A, Schneider C, Schönbach C, Sekiguchi K, Semple CAM, Seno S, Sessa L, Sheng Y, Shibata Y, Shimada H, Shimada K, Silva D, Sinclair B, Sperling S, Stupka E, Sugiura K, Sultana R, Takenaka Y, Taki K, Tammoja K, Tan SL, Tang S, Taylor MS, Tegner J, Teichmann SA, Ueda HR, van Nimwegen E, Verardo R, Wei CL, Yagi K, Yamanishi H, Zabarovsky E, Zhu S, Zimmer A, Hide W, Bult C, Grimmond SM, Teasdale RD, Liu ET, Brusic V, Quackenbush J, Wahlestedt C, Mattick JS, Hume DA, Kai C, Sasaki D, Tomaru Y, Fukuda S, Kanamori-Katayama M, Suzuki M, Aoki J, Arakawa T, Iida J, Imamura K, Itoh M, Kato T, Kawaji H, Kawagashira N, Kawashima T, Kojima M, Kondo S, Konno H, Nakano K, Ninomiya N, Nishio T, Okada M, Plessy C, Shibata K, Shiraki T, Suzuki S, Tagami M, Waki K, Watahiki A, Okamura-Oho Y, Suzuki H, Kawai J, Hayashizaki Y. The transcriptional landscape of the mammalian genome. Science 2005; 309:1559-63. [PMID: 16141072 DOI: 10.1126/science.1112014] [Citation(s) in RCA: 2607] [Impact Index Per Article: 137.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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Abstract
Complete genome data of infectious microorganisms permit systematic computational sequence-based predictions and experimental testing of candidate vaccine epitopes. Both, predictions and the interpretation of experiments rely on existing information in the literature which is mostly manually extracted and curated. The growing amount of data and literature information has created a major bottleneck for the interpretation of results and maintenance of curated databases. The lack of suitable free-text information extraction, processing, and reporting tools prompted us to develop a knowledge discovery support system that enhances the understanding of immune response and vaccine development. The current prototype system, Gene expression/epitpopes/protein interaction (GEpi), focuses on molecular functions of HIV-infected T-cells and HIV epitope information, using textmining, and interrelation of biomolecular data from domain-specific databases with MEDLINE abstract-inferred information. Results showed that extraction and processing of molecular interaction, disease associations, and gene ontology-derived functional information generate intuitive knowledge reports that aid the interpretation of host-pathogen interaction. In contrast, epitope (word and sequence) information in MEDLINE abstracts is surprisingly sparse and often lacks necessary context information, such as HLA-restriction. Since the majority of epitope information is found in tables, figures, and legends of full-text articles, its extraction may not require sophisticated natural language processing techniques. Support of vaccine development through textmining requires therefore the timely development of domain-specific extraction rules for full-text articles, and a knowledge model for epitope-related information.
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Affiliation(s)
- Christian Schönbach
- Biomedical Knowledge Discovery Team, RIKEN Genomic Sciences Center (GSC), Yokohama 230-0045, Japan.
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Abstract
Data on the major histocompatibility complex, T-cell epitopes, B-cell epitopes, antigens and diseases are heterogeneous and scattered among different databases and the literature. Since it has become increasingly difficult to obtain an integrated view of functional immune response components, we have developed and updated over several years the Functional molecular IMMunology (FIMM) database (http:// research.i2r.a-star.edu.sg/fimm/). FIMM contains integrated expert-curated data on protein antigens, and on human immunological receptors that recognise and bind them in healthy or disease states. Interfaces with multiple, intuitive query options and query reports provide immunologists with prioritised information that aids data interpretation, vaccine target discovery and immune disease research.
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Silva DG, Schönbach C, Brusic V, Socha LA, Nagashima T, Petrovsky N. Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system. BMC Genomics 2004; 5:28. [PMID: 15115540 PMCID: PMC420239 DOI: 10.1186/1471-2164-5-28] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2003] [Accepted: 04/29/2004] [Indexed: 11/24/2022] Open
Abstract
Background A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term "patholog" to mean a homolog of a human disease-related gene encoding a product (transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity (70–85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool (FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic (53%), hereditary (24%), immunological (5%), cardio-vascular (4%), or other (14%), disorders. Conclusions Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.
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Affiliation(s)
- Diego G Silva
- Medical Informatics Centre, University of Canberra, ACT 2601 Australia
- John Curtin School of Medical Research, Australian National University, Canberra ACT 2601, Australia
| | - Christian Schönbach
- Biomedical Knowledge Discovery Team, Bioinformatics Group, RIKEN Genomic Sciences Center, Yokohama 230-0045, Japan
| | | | - Luis A Socha
- Medical Informatics Centre, University of Canberra, ACT 2601 Australia
- John Curtin School of Medical Research, Australian National University, Canberra ACT 2601, Australia
| | - Takeshi Nagashima
- Biomedical Knowledge Discovery Team, Bioinformatics Group, RIKEN Genomic Sciences Center, Yokohama 230-0045, Japan
| | - Nikolai Petrovsky
- Medical Informatics Centre, University of Canberra, ACT 2601 Australia
- John Curtin School of Medical Research, Australian National University, Canberra ACT 2601, Australia
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Petrovsky N, Schönbach C, Brusic V. Bioinformatic strategies for better understanding of immune function. In Silico Biol 2004; 3:411-6. [PMID: 12954084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
Novartis Foundation sponsored a Symposium which brought together a group of experimental immunologists, theoretical immunologists, and bioinformaticians to discuss the new field of immunoinformatics. The discussion focused on immunological databases, antigen processing and presentation, immunogenomics, host-pathogen interactions, and mathematical modelling of the immune system. A main conclusion of the meeting is the critical role played by immunoinformatics in current immunology research. In particular, immunoinformatics provides a foundation for the emerging fields of systems immunology and immunogenomics.
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Affiliation(s)
- Nikolai Petrovsky
- Centre for Medical Informatics, Division of Science and Design, University of Canberra, Bruce ACT 2617, Australia.
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Nagashima T, Matsuda H, Silva DG, Petrovsky N, Konagaya A, Schönbach C, Kasukawa T, Arakawa T, Carninci P, Kawai J, Hayashizaki Y. FREP: a database of functional repeats in mouse cDNAs. Nucleic Acids Res 2004; 32:D471-5. [PMID: 14681460 PMCID: PMC308857 DOI: 10.1093/nar/gkh123] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The FREP database (http://facts.gsc.riken.go.jp/FREP/) contains 31 396 RepeatMasker-identified non-redundant variant repeat sequences derived from 16,527 mouse cDNAs with protein-coding potential. The repeats were computationally associated with potential effects on transcriptional variation, translation, protein function or involvement in disease to identify Functional REPeats (FREPs). FREPs are defined by the (i) occurrence of exon-exon boundaries in repeats, (ii) presence of polyadenylation sites in 3'UTR-located repeats, (iii) effect on translation, (iv) position in the protein- coding region or protein domains or (v) conditional association with disease MeSH terms. Currently the database contains 9261 (29.5%) inferred FREPs derived from 6861 (41.5%) mouse cDNAs. Integrated evidence of the functional assignments and dynamically generated sequence similarity search results support the exploration and annotation of functional, ancestral or taxon-specific repeats. Keyword and pre-selected feature searches (e.g. coding sequence-repeat or splice site-repeat relations) support intuitive database querying as well as the retrieval of repeat sequences. Integrated sequence search and alignment tools allow the analysis of known or identification of new functional repeat candidates. FREP is a unique resource for illuminating the role of transposons and repetitive sequences in shaping the coding part of the mouse transcriptome and for selecting the appropriate experimental model to study diseases with suspected repeat etiology contributions.
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Affiliation(s)
- Takeshi Nagashima
- Biomedical Knowledge Discovery Team, Bioinformatics Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
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39
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Abstract
The back-to-back release of the mouse genome and the functionally annotated RIKEN mouse full-length cDNA collection was an important milestone in mammalian genomics. Yet much of the data remain to be explored in terms of biological effects and mechanisms. For example, interspersed repeats account for 39 per cent of the mouse genome sequence and 11 per cent of representative transcripts. A considerable number of transposable repeat elements are still active and propagating in mouse compared with human. While existing repeat databases and tools assist the classification of repeats or identification of new repeats, there is little bioinformatic support towards exploring the extent and role of repeats in transcriptional variation, modulation of protein function, or gene regulatory events. Since the mouse is used as a model organism to study human genes and their disease associations, this review focuses on information extraction and collation that captures the functional context of repeats in mouse transcripts to facilitate the biological interpretation and extrapolation of findings to the human.
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Affiliation(s)
- Christian Schönbach
- RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi, Kanagawa 230-0045, Japan.
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Nagashima T, Silva DG, Petrovsky N, Socha LA, Suzuki H, Saito R, Kasukawa T, Kurochkin IV, Konagaya A, Schönbach C. Inferring higher functional information for RIKEN mouse full-length cDNA clones with FACTS. Genome Res 2003; 13:1520-33. [PMID: 12819151 PMCID: PMC403704 DOI: 10.1101/gr.1019903] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2002] [Accepted: 03/04/2003] [Indexed: 01/22/2023]
Abstract
FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence Sources) is a semiautomated knowledge discovery and annotation system that integrates molecular function information derived from sequence analysis results (sequence inferred) with functional information extracted from text. Text-inferred information was extracted from keyword-based retrievals of MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN mouse cDNA FANTOM2 clone annotations were informative for text searches. MEDLINE queries yielded molecular interaction-containing sentences for 23.1% of the clones. When disease MeSH and GO terms were matched with retrieved abstracts, 22.7% of clones were associated with potential diseases, and 32.5% with GO identifiers. A significant number (23.5%) of disease MeSH-associated clones were also found to have a hereditary disease association (OMIM Morbidmap). Inferred neoplastic and nervous system disease represented 49.6% and 36.0% of disease MeSH-associated clones, respectively. A comparison of sequence-based GO assignments with informative text-based GO assignments revealed that for 78.2% of clones, identical GO assignments were provided for that clone by either method, whereas for 21.8% of clones, the assignments differed. In contrast, for OMIM assignments, only 28.5% of clones had identical sequence-based and text-based OMIM assignments. Sequence, sentence, and term-based functional associations are included in the FACTS database (http://facts.gsc.riken.go.jp/), which permits results to be annotated and explored through web-accessible keyword and sequence search interfaces. The FACTS database will be a critical tool for investigating the functional complexity of the mouse transcriptome, cDNA-inferred interactome (molecular interactions), and pathome (pathologies).
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Affiliation(s)
- Takeshi Nagashima
- Biomedical Knowledge Discovery Team, Bioinformatics Group, RIKEN Genomic Sciences Center (GSC), Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
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41
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Abstract
To identify novel cytokine-related genes, we searched the set of 60,770 annotated RIKEN mouse cDNA clones (FANTOM2 clones), using keywords such as cytokine itself or cytokine names (such as interferon, interleukin, epidermal growth factor, fibroblast growth factor, and transforming growth factor). This search produced 108 known cytokines and cytokine-related products such as cytokine receptors, cytokine-associated genes, or their products (enhancers, accessory proteins, cytokine-induced genes). We found 15 clusters of FANTOM2 clones that are candidates for novel cytokine-related genes. These encoded products with strong sequence similarity to guanylate-binding protein (GBP-5), interleukin-1 receptor-associated kinase 2 (IRAK-2), interleukin 20 receptor alpha isoform 3, a member of the interferon-inducible proteins of the Ifi 200 cluster, four members of the membrane-associated family 1-8 of interferon-inducible proteins, one p27-like protein, and a hypothetical protein containing a Toll/Interleukin receptor domain. All four clones representing novel candidates of gene products from the family contain a novel highly conserved cross-species domain. Clones similar to growth factor-related products included transforming growth factor beta-inducible early growth response protein 2 (TIEG-2), TGFbeta-induced factor 2, integrin beta-like 1, latent TGF-binding protein 4S, and FGF receptor 4B. We performed a detailed sequence analysis of the candidate novel genes to elucidate their likely functional properties.
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42
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Silva DG, Schönbach C, Brusic V, Socha LA, Nagashima T, Petrovsky N. Identification of Novel “Pathologs” (Human Disease-Related Gene Candidates) From the RIKEN Full-Length Mouse cDNA Data Set. Genome Res 2003. [DOI: 10.1101/gr.1461303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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43
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Kanapin A, Batalov S, Davis MJ, Gough J, Grimmond S, Kawaji H, Magrane M, Matsuda H, Schönbach C, Teasdale RD, Yuan Z. Mouse proteome analysis. Genome Res 2003; 13:1335-44. [PMID: 12819131 PMCID: PMC403658 DOI: 10.1101/gr.978703] [Citation(s) in RCA: 77] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2002] [Accepted: 03/05/2003] [Indexed: 11/25/2022]
Abstract
A general overview of the protein sequence set for the mouse transcriptome produced during the FANTOM2 sequencing project is presented here. We applied different algorithms to characterize protein sequences derived from a nonredundant representative protein set (RPS) and a variant protein set (VPS) of the mouse transcriptome. The functional characterization and assignment of Gene Ontology terms was done by analysis of the proteome using InterPro. The Superfamily database analyses gave a detailed structural classification according to SCOP and provide additional evidence for the functional characterization of the proteome data. The MDS database analysis revealed new domains which are not presented in existing protein domain databases. Thus the transcriptome gives us a unique source of data for the detection of new functional groups. The data obtained for the RPS and VPS sets facilitated the comparison of different patterns of protein expression. A comparison of other existing mouse and human protein sequence sets (e.g., the International Protein Index) demonstrates the common patterns in mammalian proteomes. The analysis of the membrane organization within the transcriptome of multiple eukaryotes provides valuable statistics about the distribution of secretory and transmembrane proteins
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Affiliation(s)
- Alexander Kanapin
- EMBL Outstation-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK.
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Suzuki H, Saito R, Kanamori M, Kai C, Schönbach C, Nagashima T, Hosaka J, Hayashizaki Y. The mammalian protein-protein interaction database and its viewing system that is linked to the main FANTOM2 viewer. Genome Res 2003; 13:1534-41. [PMID: 12819152 PMCID: PMC403706 DOI: 10.1101/gr.956303] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Here, we describe the development of a mammalian protein-protein interaction (PPI) database and of a PPI Viewer application to display protein interaction networks (http://fantom21.gsc.riken.go.jp/PPI/). In the database, we stored the mammalian PPIs identified through our PPI assays (internal PPIs), as well as those we extracted and processed (external PPIs) from publicly available data sources, the DIP and BIND databases and MEDLINE abstracts by using FACTS, a new functional inference and curation system. We integrated the internal and external PPIs into the PPI database, which is linked to the main FANTOM2 viewer. In addition, we incorporated into the PPI Viewer information regarding the luciferase reporter activity of internal PPIs and the data confidence of external PPIs; these data enable visualization and evaluation of the reliability of each interaction. Using the described system, we successfully identified several interactions of biological significance. Therefore, the PPI Viewer is a useful tool for exploring FANTOM2 clone-related protein interactions and their potential effects on signaling and cellular communication.
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Affiliation(s)
- Harukazu Suzuki
- Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
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Schönbach C. From immunogenetics to immunomics: functional prospecting of genes and transcripts. Novartis Found Symp 2003; 254:177-88; discussion 189-92, 216-22, 250-2. [PMID: 14712938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/27/2023]
Abstract
Human and mouse genome and transcriptome projects have expanded the field of 'immunogenetics' beyond the traditional study of the genetics and evolution of MHC, TCR and Ig loci into the new interdisciplinary area of 'immunomics'. Immunomics is the study of the molecular functions associated with all immune-related coding and non-coding mRNA transcripts. To unravel the function, regulation and diversity of the immunome requires that we identify and correctly categorize all immune-related transcripts. The importance of intercalated genes, antisense transcripts and non-coding RNAs and their potential role in regulation of immune development and function are only just starting to be appreciated. To better understand immune function and regulation, transcriptome projects (e.g. Functional Annotation of the Mouse, FANTOM), that focus on sequencing full-length transcripts from multiple tissue sources, ideally should include specific immune cells (e.g. T cell, B cells, macrophages, dendritic cells) at various states of development, in activated and unactivated states and in different disease contexts. Progress in deciphering immune regulatory networks will require the cooperative efforts of immunologists, immunogeneticists, molecular biologists and bioinformaticians. Although primary sequence analysis remains useful for annotation of new transcripts it is less useful for identifying novel functions of known transcripts in a new context (protein interaction network or pathway). The most efficient approach to mine useful information from the vast a priori knowledge contained in biological databases and the scientific literature, is to use a combination of computational and expert-driven knowledge discovery strategies. This paper will illustrate the challenges posed in attempts to functionally infer transcriptional regulation and interaction of immune-related genes from text and sequence-based data sources.
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Affiliation(s)
- Christian Schönbach
- Biomedical Knowledge Discovery Team, Bioinformatics Group, RIKEN Genomic Sciences Center (GSC), 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan
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46
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Okazaki Y, Furuno M, Kasukawa T, Adachi J, Bono H, Kondo S, Nikaido I, Osato N, Saito R, Suzuki H, Yamanaka I, Kiyosawa H, Yagi K, Tomaru Y, Hasegawa Y, Nogami A, Schönbach C, Gojobori T, Baldarelli R, Hill DP, Bult C, Hume DA, Quackenbush J, Schriml LM, Kanapin A, Matsuda H, Batalov S, Beisel KW, Blake JA, Bradt D, Brusic V, Chothia C, Corbani LE, Cousins S, Dalla E, Dragani TA, Fletcher CF, Forrest A, Frazer KS, Gaasterland T, Gariboldi M, Gissi C, Godzik A, Gough J, Grimmond S, Gustincich S, Hirokawa N, Jackson IJ, Jarvis ED, Kanai A, Kawaji H, Kawasawa Y, Kedzierski RM, King BL, Konagaya A, Kurochkin IV, Lee Y, Lenhard B, Lyons PA, Maglott DR, Maltais L, Marchionni L, McKenzie L, Miki H, Nagashima T, Numata K, Okido T, Pavan WJ, Pertea G, Pesole G, Petrovsky N, Pillai R, Pontius JU, Qi D, Ramachandran S, Ravasi T, Reed JC, Reed DJ, Reid J, Ring BZ, Ringwald M, Sandelin A, Schneider C, Semple CAM, Setou M, Shimada K, Sultana R, Takenaka Y, Taylor MS, Teasdale RD, Tomita M, Verardo R, Wagner L, Wahlestedt C, Wang Y, Watanabe Y, Wells C, Wilming LG, Wynshaw-Boris A, Yanagisawa M, Yang I, Yang L, Yuan Z, Zavolan M, Zhu Y, Zimmer A, Carninci P, Hayatsu N, Hirozane-Kishikawa T, Konno H, Nakamura M, Sakazume N, Sato K, Shiraki T, Waki K, Kawai J, Aizawa K, Arakawa T, Fukuda S, Hara A, Hashizume W, Imotani K, Ishii Y, Itoh M, Kagawa I, Miyazaki A, Sakai K, Sasaki D, Shibata K, Shinagawa A, Yasunishi A, Yoshino M, Waterston R, Lander ES, Rogers J, Birney E, Hayashizaki Y. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature 2002; 420:563-73. [PMID: 12466851 DOI: 10.1038/nature01266] [Citation(s) in RCA: 1226] [Impact Index Per Article: 55.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2002] [Accepted: 10/28/2002] [Indexed: 01/10/2023]
Abstract
Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.
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MESH Headings
- Alternative Splicing/genetics
- Amino Acid Motifs
- Animals
- Chromosomes, Mammalian/genetics
- Cloning, Molecular
- DNA, Complementary/genetics
- Databases, Genetic
- Expressed Sequence Tags
- Genes/genetics
- Genomics/methods
- Humans
- Membrane Proteins/genetics
- Mice/genetics
- Physical Chromosome Mapping
- Protein Structure, Tertiary
- Proteome/chemistry
- Proteome/genetics
- RNA, Antisense/genetics
- RNA, Messenger/analysis
- RNA, Messenger/genetics
- RNA, Untranslated/analysis
- RNA, Untranslated/genetics
- Transcription Initiation Site
- Transcription, Genetic/genetics
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Affiliation(s)
- Y Okazaki
- [1] Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
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Abstract
Bioinformatics-driven T-cell epitope-identification methods can enhance vaccine target selection significantly. We evaluated three unrelated computational methods to screen Pol, Gag and Env sequences extracted from the Los Alamos HIV database for HLA-A*0201 and HLA-B*3501 T-cell epitope candidates. The hidden Markov model predicted 389 HLA-B*3501-restricted candidates from 374 HIV-1 and 97 HIV-2 sequences. The artificial neural network (ANN) model, and Bioinformatics and Molecular Analysis Section (BIMAS) quantitative matrix predictions for A*0201 yielded 1122 HIV-1 and 548 HIV-2 candidates. The overall sequence coverage of the predicted A*0201 T-cell epitopes was 2.7% (HIV-1)and 3.0% (HIV-2). HLA-B*3501-predicted epitopes covered 0.9% (HIV-1) and 1.4% (HIV-2) of the total sequence. Comparison of 890 ANN- and 397 BIMAS-derived HIV-1 A*0201- restricted epitope candidates showed that only 13-19% of the predicted and 26% of the experimentally confirmed T-cell epitopes were captured by both methods. Extrapolating these results, we estimated that at least 247 predicted HIV-1 epitopes are yet to be discovered as active A*0201-restricted T-cell epitopes. Adequate comparison and combined usage of various predictive bioinformatics methods, rather than uncritical use of any single prediction method, will enable cost-effective and efficient T-cell epitope screening.
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48
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Yu K, Petrovsky N, Schönbach C, Koh JLY, Brusic V. Methods for Prediction of Peptide Binding to MHC Molecules: A Comparative Study. Mol Med 2002. [DOI: 10.1007/bf03402006] [Citation(s) in RCA: 95] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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Abstract
We performed a systematic maximum density subgraph (MDS) detection of conserved sequence regions to discover new, biologically relevant motifs from a set of 21,050 conceptually translated mouse cDNA (FANTOM1) sequences. A total of 3202 candidate sequences, which shared similar regions over >20 amino acid residues, were screened against known conserved regions listed in Pfam, ProDom, and InterPro. The filtering procedure resulted in 139 FANTOM1 sequences belonging to 49 new motif candidates. Using annotations and multiple sequence alignment information, we removed by visual inspection 42 candidates whose members were found to be false positives because of sequence redundancy, alternative splicing, low complexity, transcribed retroviral repeat elements contained in the region of the predicted open reading frame, and reports in the literature. The remaining seven motifs have been expanded by hidden Markov model (HMM) profile searches of SWISS-PROT/TrEMBL from 28 FANTOM1 sequences to 164 members and analyzed in detail on sequence and structure level to elucidate the possible functions of motifs and members. The novel and conserved motif MDS00105 is specific for the mammalian inhibitor of growth (ING) family. Three submotifs MDS00105.1-3 are specific for ING1/ING1L, ING1-homolog, and ING3 subfamilies. The motif MDS00105 together with a PHD finger domain constitutes a module for ING proteins. Structural motif MDS00113 represents a leucine zipper-like motif. Conserved motif MDS00145 is a novel 1-acyl-SN-glycerol-3-phosphate acyltransferase (AGPAT) submotif containing a transmembrane domain that distinguishes AGPAT3 and AGPAT4 from all other acyltransferase domain-containing proteins. Functional motif MDS00148 overlaps with the kazal-type serine protease inhibitor domain but has been detected only in an extracellular loop region of solute carrier 21 (SLC21) (organic anion transporters) family members, which may regulate the specificity of anion uptake. Our motif discovery not only aided in the functional characterization of new mouse orthologs for potential drug targets but also allowed us to predict that at least 16 other new motifs are waiting to be discovered from the current SWISS-PROT/TrEMBL database.
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Affiliation(s)
- Hideya Kawaji
- Department of Informatics and Mathematical Science, Graduate School of Engineering Science, Osaka University, Toyonaka 560-8531, Japan
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50
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Brusic V, Bucci K, Schönbach C, Petrovsky N, Zeleznikow J, Kazura JW. Efficient discovery of immune response targets by cyclical refinement of QSAR models of peptide binding. J Mol Graph Model 2002; 19:405-11, 467. [PMID: 11552688 DOI: 10.1016/s1093-3263(00)00099-1] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-A11 binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes.
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Affiliation(s)
- V Brusic
- BIC-KRDL, Kent Ridge Digital Labs, 21 Heng Mui Keng Terrace, Singapore 119613.
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