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Nakatsu K, Jijiwa M, Khadka V, Nasu M, Deng Y. sRNAfrag: a pipeline and suite of tools to analyze fragmentation in small RNA sequencing data. Brief Bioinform 2023; 25:bbad515. [PMID: 38243693 PMCID: PMC10796253 DOI: 10.1093/bib/bbad515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 11/25/2023] [Accepted: 12/13/2023] [Indexed: 01/21/2024] Open
Abstract
Fragments derived from small RNAs such as small nucleolar RNAs are biologically relevant but remain poorly understood. To address this gap, we developed sRNAfrag, a modular and interoperable tool designed to standardize the quantification and analysis of small RNA fragmentation across various biotypes. The tool outputs a set of tables forming a relational database, allowing for an in-depth exploration of biologically complex events such as multi-mapping and RNA fragment stability across different cell types. In a benchmark test, sRNAfrag was able to identify established loci of mature microRNAs solely based on sequencing data. Furthermore, the 5' seed sequence could be rediscovered by utilizing a visualization approach primarily applied in multi-sequence-alignments. Utilizing the relational database outputs, we detected 1411 snoRNA fragment conservation events between two out of four eukaryotic species, providing an opportunity to explore motifs through evolutionary time and conserved fragmentation patterns. Additionally, the tool's interoperability with other bioinformatics tools like ViennaRNA amplifies its utility for customized analyses. We also introduce a novel loci-level variance-score which provides insights into the noise around peaks and demonstrates biological relevance by distinctly separating breast cancer and neuroblastoma cell lines after dimension reduction when applied to small nucleolar RNAs. Overall, sRNAfrag serves as a versatile foundation for advancing our understanding of small RNA fragments and offers a functional foundation to further small RNA research. Availability: https://github.com/kenminsoo/sRNAfrag.
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Affiliation(s)
- Ken Nakatsu
- Emory College of Arts and Sciences, Emory University, 201 Dowman Dr, 30322, Georgia, United States of America
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, 96813, Hawaii, United States of America
| | - Mayumi Jijiwa
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, 96813, Hawaii, United States of America
| | - Vedbar Khadka
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, 96813, Hawaii, United States of America
| | - Masaki Nasu
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, 96813, Hawaii, United States of America
| | - Youping Deng
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, 96813, Hawaii, United States of America
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2
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Nakatsu K, Jijiwa M, Khadka V, Nasu M, Huo M, Deng Y. sRNAfrag: A pipeline and suite of tools to analyze fragmentation in small RNA sequencing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.19.553943. [PMID: 37662282 PMCID: PMC10473647 DOI: 10.1101/2023.08.19.553943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Fragments derived from small RNAs such as small nucleolar RNAs hold biological relevance. However, they remain poorly understood, calling for more comprehensive methods for analysis. We developed sRNAfrag, a standardized workflow and set of scripts to quantify and analyze sRNA fragmentation of any biotype. In a benchmark, it is able to detect loci of mature microRNAs fragmented from precursors and, utilizing multi-mapping events, the conserved 5' seed sequence of miRNAs which we believe may extraoplate to other small RNA fragments. The tool detected 1411 snoRNA fragment conservation events between 2/4 eukaryotic species, providing the opportunity to explore motifs and fragmentation patterns not only within species, but between. Availability: https://github.com/kenminsoo/sRNAfrag.
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Affiliation(s)
- Ken Nakatsu
- Emory College of Arts and Sciences, Emory University, 201 Dowman Dr, Atlanta, 30322, Georgia, United States of America
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, Honolulu, 96813, Hawaii, United States of America
| | - Mayumi Jijiwa
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, Honolulu, 96813, Hawaii, United States of America
| | - Vedbar Khadka
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, Honolulu, 96813, Hawaii, United States of America
| | - Masaki Nasu
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, Honolulu, 96813, Hawaii, United States of America
| | - Matthew Huo
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, Honolulu, 96813, Hawaii, United States of America
- Krieger School of Arts and Sciences, Johns Hopkins University, 3400 N Charles St, Baltimore, 21218, Maryland, United States of America
| | - Youping Deng
- Department of Quantitative Health Sciences, University of Hawaii John A. Burns School of Medicine, 651 Ilalo St, Honolulu, 96813, Hawaii, United States of America
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3
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Bioinformatics in Mexico: A diagnostic from the academic perspective and recommendations for a public policy. PLoS One 2020; 15:e0243531. [PMID: 33320879 PMCID: PMC7737905 DOI: 10.1371/journal.pone.0243531] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 11/24/2020] [Indexed: 11/19/2022] Open
Abstract
In this work, we present a diagnostic analysis of strengths, weaknesses, opportunities and threats (SWOT) of the current state of Bioinformatics in Mexico. We conducted semi-structured interviews among researchers and academics with key expertise in this field, identified by bibliometric analyses and qualitative sampling techniques. Additionally, an online survey was conducted reaching a higher number of respondents. Among the relevant findings of our study, the lack of specialized human resources and technological infrastructure stood out, along with deficiencies in the number and quality of academic programs, scarce public investment and a weak relationship between public and private institutions. However, there are great opportunities for developing a national Bioinformatics to support different economic sectors. In our opinion, this work could be useful to favor a comprehensive network among Mexican researchers, in order to lay the foundations of a national strategy towards a well designed public policy.
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Hosmani PS, Shippy T, Miller S, Benoit JB, Munoz-Torres M, Flores-Gonzalez M, Mueller LA, Wiersma-Koch H, D’Elia T, Brown SJ, Saha S. A quick guide for student-driven community genome annotation. PLoS Comput Biol 2019; 15:e1006682. [PMID: 30943207 PMCID: PMC6447164 DOI: 10.1371/journal.pcbi.1006682] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
High quality gene models are necessary to expand the molecular and genetic tools available for a target organism, but these are available for only a handful of model organisms that have undergone extensive curation and experimental validation over the course of many years. The majority of gene models present in biological databases today have been identified in draft genome assemblies using automated annotation pipelines that are frequently based on orthologs from distantly related model organisms and usually have minor or major errors. Manual curation is time consuming and often requires substantial expertise, but is instrumental in improving gene model structure and identification. Manual annotation may seem to be a daunting and cost-prohibitive task for small research communities but involving undergraduates in community genome annotation consortiums can be mutually beneficial for both education and improved genomic resources. We outline a workflow for efficient manual annotation driven by a team of primarily undergraduate annotators. This model can be scaled to large teams and includes quality control processes through incremental evaluation. Moreover, it gives students an opportunity to increase their understanding of genome biology and to participate in scientific research in collaboration with peers and senior researchers at multiple institutions.
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Affiliation(s)
| | - Teresa Shippy
- Division of Biology, Kansas State University, Manhattan, Kansas
| | - Sherry Miller
- Division of Biology, Kansas State University, Manhattan, Kansas
| | - Joshua B. Benoit
- Department of Biological Sciences, University of Cincinnati, Cincinnati, Ohio
| | - Monica Munoz-Torres
- Lawrence Berkeley National Laboratory, Environmental Genomics and Systems Biology, Berkeley, California
- Center for Genome Research and Biocomputing, Oregon State University, Corvallis, Oregon
| | | | | | | | - Tom D’Elia
- Indian River State College, Fort Pierce, Florida
| | - Susan J. Brown
- Division of Biology, Kansas State University, Manhattan, Kansas
| | - Surya Saha
- Boyce Thompson Institute, Ithaca, New York
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5
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Wheeler TR, Oxley PR. Developing a Library Bioinformatics Program Fully Integrated into a Medical Research Institution. Med Ref Serv Q 2019; 37:413-421. [PMID: 30722773 DOI: 10.1080/02763869.2018.1514915] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Establishment of a new bioinformatics service at the Samuel J. Wood Library of Weill Cornell Medicine was successfully achieved through reference to existing programs and utilization of established success factors. Setting the vision, focusing on the essentials, designing for value, and implementing continuous improvement through feedback, helped to create a successful and integrated bioinformatics service for the medical research community.
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6
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Stevens SLR, Kuzak M, Martinez C, Moser A, Bleeker P, Galland M. Building a local community of practice in scientific programming for life scientists. PLoS Biol 2018; 16:e2005561. [PMID: 30485260 PMCID: PMC6287879 DOI: 10.1371/journal.pbio.2005561] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 12/10/2018] [Indexed: 11/18/2022] Open
Abstract
In this paper, we describe why and how to build a local community of practice in scientific programming for life scientists who use computers and programming in their research. A community of practice is a small group of scientists who meet regularly to help each other and promote good practices in scientific programming. While most life scientists are well trained in the laboratory to conduct experiments, good practices with (big) data sets and their analysis are often missing. We propose a model on how to build such a community of practice at a local academic institution, present two real-life examples, and introduce challenges and implemented solutions. We believe that the current data deluge that life scientists face can benefit from the implementation of these small communities. Good practices spread among experimental scientists will foster open, transparent, and sound scientific results beneficial to society.
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Affiliation(s)
- Sarah L. R. Stevens
- Department of Bacteriology, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Mateusz Kuzak
- Dutch Techcentre for Life Sciences, Utrecht, Netherlands
| | | | - Aurelia Moser
- Mozilla Foundation, Mountain View, California, United States of America
| | - Petra Bleeker
- Department of Plant Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Marc Galland
- Department of Plant Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
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7
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Abstract
Ever return from a meeting feeling elated by all those exciting talks, yet unsure how all those presented glamorous and/or exciting tools can be useful in your research? Or do you have a great piece of software you want to share, yet only a handful of people visited your poster? We have all been there, and that is why we organized the Matchmaking for Computational and Experimental Biologists Session at the latest ISCB/GLBIO’2017 meeting in Chicago (May 15-17, 2017). The session exemplifies a novel approach, mimicking “matchmaking”, to encouraging communication, making connections and fostering collaborations between computational and non-computational biologists. More specifically, the session facilitates face-to-face communication between researchers with similar or differing research interests, which we feel are critical for promoting productive discussions and collaborations. To accomplish this, three short scheduled talks were delivered, focusing on RNA-seq, integration of clinical and genomic data, and chromatin accessibility analyses. Next, small-table developer-led discussions, modeled after speed-dating, enabled each developer (including the speakers) to introduce a specific tool and to engage potential users or other developers around the table. Notably, we asked the audience whether any other tool developers would want to showcase their tool and we thus added four developers as moderators of these small-table discussions. Given the positive feedback from the tool developers, we feel that this type of session is an effective approach for promoting valuable scientific discussion, and is particularly helpful in the context of conferences where the number of participants and activities could hamper such interactions.
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Affiliation(s)
- Ewy Mathé
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
| | - Ben Busby
- National Center for Biotechnology Information (NCBI), National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Helen Piontkivska
- Department of Biological Sciences and School of Biomedical Sciences, Kent State University, Kent, OH, 44242, USA
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Biscarini F, Cozzi P, Orozco-Ter Wengel P. Lessons learnt on the analysis of large sequence data in animal genomics. Anim Genet 2018; 49:147-158. [PMID: 29624711 DOI: 10.1111/age.12655] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/11/2018] [Indexed: 11/28/2022]
Abstract
The 'omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human 'omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next-generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large-scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry-the software may crash or stop-and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets.
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Affiliation(s)
- F Biscarini
- CNR-IBBA, Via Bassini 15, 20133, Milan, Italy.,School of Medicine, Cardiff University, Heath Park, CF14 4XN, Cardiff, UK
| | - P Cozzi
- CNR-IBBA, Via Bassini 15, 20133, Milan, Italy.,Department of Bioinformatics and Biostatistics, PTP Science Park, Via Einstein, 26900, Lodi, Italy
| | - P Orozco-Ter Wengel
- School of Biosciences, Cardiff University, Museum Avenue, CF10 3AX, Cardiff, UK
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9
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Anupama J, Francescatto M, Rahman F, Fatima N, DeBlasio D, Shanmugam AK, Satagopam V, Santos A, Kolekar P, Michaut M, Guney E. The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide. PLoS Comput Biol 2018; 14:e1005802. [PMID: 29346365 PMCID: PMC5772997 DOI: 10.1371/journal.pcbi.1005802] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one’s field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one’s research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.
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Affiliation(s)
- Jigisha Anupama
- University College Dublin, Dublin, Ireland
- * E-mail: (JA); (EG)
| | | | - Farzana Rahman
- Genomics and Computational Biology Group, School of Computing and Mathematics, University of South Wales, Treforest, Wales, United Kingdom
| | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Dan DeBlasio
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | | | - Venkata Satagopam
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Luxembourg City, Luxembourg
| | - Alberto Santos
- Novo Nordisk Foundation Center for Protein Research, Copenhagen, Denmark
| | | | - Magali Michaut
- The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Emre Guney
- Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine, Barcelona, Catalonia, Spain
- * E-mail: (JA); (EG)
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10
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Rasheed Z. Bioinformatics approach: A powerful tool for microRNA research. Int J Health Sci (Qassim) 2017; 11:1-3. [PMID: 28936142 PMCID: PMC5604275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Zafar Rasheed
- Department of Medical Biochemistry, College of Medicine, Qassim University, Buraidah, Saudi Arabia,Address for correspondence: Zafar Rasheed, MS., Ph.D., PGDCA. Section Editor, International Journal of Health Sciences, Department of Medical Biochemistry, College of Medicine, Qassim University, P.O. Box 6655, Buraidah-51452, Saudi Arabia. E-mail:
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11
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White B, Fatima V, Fatima N, Das S, Rahman F, Hassan M. Highlights of the 2 (nd) Bioinformatics Student Symposium by ISCB RSG-UK. F1000Res 2016; 5. [PMID: 27239284 PMCID: PMC4870987 DOI: 10.12688/f1000research.8445.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/13/2016] [Indexed: 11/25/2022] Open
Abstract
Following the success of the 1
st Student Symposium by ISCB RSG-UK, a 2
nd Student Symposium took place on 7
th October 2015 at The Genome Analysis Centre, Norwich, UK. This short report summarizes the main highlights from the 2
nd Bioinformatics Student Symposium.
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Affiliation(s)
| | - Vayani Fatima
- Algorithms and Bioinformatics Group, King's College London, London, UK
| | - Nazeefa Fatima
- Eukaryotic Evolution Research Group, University of Huddersfield, Huddersfield, UK
| | - Sayoni Das
- Research Department of Structural and Molecular Biology, University College London, London, UK
| | - Farzana Rahman
- School of Computing and Mathematics, University of South Wales, Cardiff, UK
| | - Mehedi Hassan
- School of Computing and Mathematics, University of South Wales, Cardiff, UK
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12
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Abstract
Development of free/libre open source software is usually done by a community of people with an interest in the tool. For scientific software, however, this is less often the case. Most scientific software is written by only a few authors, often a student working on a thesis. Once the paper describing the tool has been published, the tool is no longer developed further and is left to its own device. Here we describe the broad, multidisciplinary community we formed around a set of tools for statistical genomics. The GenABEL project for statistical omics actively promotes open interdisciplinary development of statistical methodology and its implementation in efficient and user-friendly software under an open source licence. The software tools developed withing the project collectively make up the GenABEL suite, which currently consists of eleven tools. The open framework of the project actively encourages involvement of the community in all stages, from formulation of methodological ideas to application of software to specific data sets. A web forum is used to channel user questions and discussions, further promoting the use of the GenABEL suite. Developer discussions take place on a dedicated mailing list, and development is further supported by robust development practices including use of public version control, code review and continuous integration. Use of this open science model attracts contributions from users and developers outside the “core team”, facilitating agile statistical omics methodology development and fast dissemination.
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Affiliation(s)
- Lennart C Karssen
- PolyOmica, Groningen, 9722 HC, Netherlands; Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3000 CA, Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3000 CA, Netherlands
| | - Yurii S Aulchenko
- PolyOmica, Groningen, 9722 HC, Netherlands; Institute of Cytology and Genetics, Siberian Division of the Russian Academy of Sciences, Novosibirsk, 630090, Russian Federation; Novosibirsk State University, Novosibirsk, 630090, Russian Federation; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
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13
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Ramsay M, Sankoh O. African partnerships through the H3Africa Consortium bring a genomic dimension to longitudinal population studies on the continent. Int J Epidemiol 2016; 45:305-8. [PMID: 26659658 PMCID: PMC5841636 DOI: 10.1093/ije/dyv187] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience and Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa,
| | - Osman Sankoh
- INDEPTH Network, Kanda, Accra, Ghana and Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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14
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Chimusa ER, Mbiyavanga M, Masilela V, Kumuthini J. "Broadband" Bioinformatics Skills Transfer with the Knowledge Transfer Programme (KTP): Educational Model for Upliftment and Sustainable Development. PLoS Comput Biol 2015; 11:e1004512. [PMID: 26583922 PMCID: PMC4652891 DOI: 10.1371/journal.pcbi.1004512] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
A shortage of practical skills and relevant expertise is possibly the primary obstacle to social upliftment and sustainable development in Africa. The "omics" fields, especially genomics, are increasingly dependent on the effective interpretation of large and complex sets of data. Despite abundant natural resources and population sizes comparable with many first-world countries from which talent could be drawn, countries in Africa still lag far behind the rest of the world in terms of specialized skills development. Moreover, there are serious concerns about disparities between countries within the continent. The multidisciplinary nature of the bioinformatics field, coupled with rare and depleting expertise, is a critical problem for the advancement of bioinformatics in Africa. We propose a formalized matchmaking system, which is aimed at reversing this trend, by introducing the Knowledge Transfer Programme (KTP). Instead of individual researchers travelling to other labs to learn, researchers with desirable skills are invited to join African research groups for six weeks to six months. Visiting researchers or trainers will pass on their expertise to multiple people simultaneously in their local environments, thus increasing the efficiency of knowledge transference. In return, visiting researchers have the opportunity to develop professional contacts, gain industry work experience, work with novel datasets, and strengthen and support their ongoing research. The KTP develops a network with a centralized hub through which groups and individuals are put into contact with one another and exchanges are facilitated by connecting both parties with potential funding sources. This is part of the PLOS Computational Biology Education collection.
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Affiliation(s)
- Emile R. Chimusa
- Computational Biology Group, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Velaphi Masilela
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | - Judit Kumuthini
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
- * E-mail:
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15
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Ison J, Rapacki K, Ménager H, Kalaš M, Rydza E, Chmura P, Anthon C, Beard N, Berka K, Bolser D, Booth T, Bretaudeau A, Brezovsky J, Casadio R, Cesareni G, Coppens F, Cornell M, Cuccuru G, Davidsen K, Vedova GD, Dogan T, Doppelt-Azeroual O, Emery L, Gasteiger E, Gatter T, Goldberg T, Grosjean M, Grüning B, Helmer-Citterich M, Ienasescu H, Ioannidis V, Jespersen MC, Jimenez R, Juty N, Juvan P, Koch M, Laibe C, Li JW, Licata L, Mareuil F, Mičetić I, Friborg RM, Moretti S, Morris C, Möller S, Nenadic A, Peterson H, Profiti G, Rice P, Romano P, Roncaglia P, Saidi R, Schafferhans A, Schwämmle V, Smith C, Sperotto MM, Stockinger H, Vařeková RS, Tosatto SCE, de la Torre V, Uva P, Via A, Yachdav G, Zambelli F, Vriend G, Rost B, Parkinson H, Løngreen P, Brunak S. Tools and data services registry: a community effort to document bioinformatics resources. Nucleic Acids Res 2015; 44:D38-47. [PMID: 26538599 PMCID: PMC4702812 DOI: 10.1093/nar/gkv1116] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 10/13/2015] [Indexed: 01/24/2023] Open
Abstract
Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand. Here we present a community-driven curation effort, supported by ELIXIR—the European infrastructure for biological information—that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners. As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.
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Affiliation(s)
- Jon Ison
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | - Kristoffer Rapacki
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | - Hervé Ménager
- Centre d'Informatique pour la Biologie, C3BI, Institut Pasteur, France
| | - Matúš Kalaš
- Computational Biology Unit, Department of Informatics, University of Bergen, Norway
| | - Emil Rydza
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | - Piotr Chmura
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | - Christian Anthon
- Department of Veterinary Clinical and Animal Sciences, Faculty for Health and Medical Sciences, University of Copenhagen, Denmark
| | - Niall Beard
- School of Computer Science, University of Manchester, UK
| | - Karel Berka
- Department of Physical Chemistry, RCPTM, Faculty of Science, Palacky University, Czech Republic
| | - Dan Bolser
- The European Bioinformatics Institute (EMBL-EBI), UK
| | - Tim Booth
- NEBC Wallingford, Centre for Ecology and Hydrology, UK
| | - Anthony Bretaudeau
- INRA, UMR Institut de Génétique, Environnement et Protection des Plantes (IGEPP), BioInformatics Platform for Agroecosystems Arthropods (BIPAA), France INRIA, IRISA, GenOuest Core Facility, France
| | - Jan Brezovsky
- Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Czech Republic
| | - Rita Casadio
- Bologna Biocomputing Group, University of Bologna, Italy
| | | | - Frederik Coppens
- Department of Plant Systems Biology, VIB, Belgium Department of Plant Biotechnology and Bioinformatics, Ghent University, Belgium
| | | | | | - Kristian Davidsen
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | | | - Tunca Dogan
- UniProt, European Bioinformatics Institute (EMBL-EBI), UK
| | | | - Laura Emery
- The European Bioinformatics Institute (EMBL-EBI), UK
| | | | - Thomas Gatter
- Faculty of Technology and Center for Biotechnology, Universität Bielefeld, Germany
| | | | - Marie Grosjean
- Institut Français de Bioinformatique (French Institute of Bioinformatics), CNRS, UMS3601, France
| | - Björn Grüning
- Albert-Ludwigs-Universität Freiburg, Fahnenbergplatz, 79085 Freiburg
| | | | - Hans Ienasescu
- Bioinformatics Centre, Department of Biology, University of Copenhagen, Denmark
| | | | - Martin Closter Jespersen
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | | | - Nick Juty
- The European Bioinformatics Institute (EMBL-EBI), UK
| | - Peter Juvan
- Centre for Functional Genomics and Biochips, Faculty of Medicine, University of Ljubljana, Slovenia
| | | | - Camille Laibe
- The European Bioinformatics Institute (EMBL-EBI), UK
| | - Jing-Woei Li
- Faculty of Medicine, The Chinese University of Hong Kong, China Hong Kong Bioinformatics Centre, School of Life Sciences,The Chinese University of Hong Kong, China
| | - Luana Licata
- Dept. of Biology, University of Rome Tor Vergata, Italy
| | - Fabien Mareuil
- Centre d'Informatique pour la Biologie, C3BI, Institut Pasteur, France
| | - Ivan Mičetić
- Department of Biomedical Sciences, University of Padua, Italy
| | | | - Sebastien Moretti
- SIB Swiss Institute of Bioinformatics, Switzerland Department of Ecology and Evolution, Biophore, Evolutionary Bioinformatics group, University of Lausanne, Switzerland
| | | | - Steffen Möller
- Department of Dermatology, University of Lübeck, Germany Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Germany
| | | | - Hedi Peterson
- Institute of Computer Science, University of Tartu, Estonia
| | | | - Peter Rice
- Department of Computing, William Penney Laboratory, Imperial College London, UK
| | | | | | - Rabie Saidi
- UniProt, European Bioinformatics Institute (EMBL-EBI), UK
| | | | - Veit Schwämmle
- Protein Research Group, Department for Biochemistry and Molecular Biology, University of Southern Denmark, Denmark
| | | | - Maria Maddalena Sperotto
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | | | | | | | - Victor de la Torre
- National Bioinformatics Institute Unit (INB), Fundacion Centro Nacional de Investigaciones Oncologicas, Spain
| | | | - Allegra Via
- Dept. of Physics, Sapienza University, Italy
| | - Guy Yachdav
- Department of Informatics, Bioinformatics-I12, TUM, Germany
| | - Federico Zambelli
- Institute of Biomembranes and Bioenergetics, National Research Council (CNR), and Dept. of Biosciences, University of Milano, Italy
| | - Gert Vriend
- Radboud University Medical Centre, CMBI, Netherlands
| | - Burkhard Rost
- Department of Informatics, Bioinformatics-I12, TUM, Germany
| | | | - Peter Løngreen
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark
| | - Søren Brunak
- Center for Biological Sequence Analysis Department of Systems Biology, Technical University of Denmark, Denmark Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
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Souilmi Y, Allali I, Badad O, Dwibedi CK. Highlights of the first ISCB Student Council Symposium in Africa 2015. F1000Res 2015; 4:ISCB Comm J-569. [PMID: 26998231 PMCID: PMC4786895 DOI: 10.12688/f1000research.6877.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/04/2015] [Indexed: 11/20/2022] Open
Abstract
This is a summary of the activities and scientific content of the first International Society for Computational Biology Student Council symposium in Africa. This meeting organized by the students for the students took place 8th of March 2015 in Dar Es Salaam, Tanzania.
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Affiliation(s)
- Yassine Souilmi
- Department of Biology, Mohamed Vth University, Rabat, 110 066, Morocco
- Department of Biomedical Informatics, Harvard University, Cambridge, MA, 02138, USA
| | - Imane Allali
- Department of Biology, Mohamed Vth University, Rabat, 110 066, Morocco
| | - Oussama Badad
- Department of Biology, Mohamed Vth University, Rabat, 110 066, Morocco
| | - Chinmay Kumar Dwibedi
- Department of Clinical Microbiology, Umea University, Umea, 901 87, Sweden
- Swedish Defence Research Agency, Umea, 164 90, Sweden
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Rahman F, Farmer R, Das S, Vayani F, Hassan M. Highlights of the 1st Student Symposium of the ISCB RSG UK. F1000Res 2015; 4:154. [PMID: 26998223 PMCID: PMC4786907 DOI: 10.12688/f1000research.6616.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/10/2015] [Indexed: 11/20/2022] Open
Abstract
This short report summarises the scientific content and activities of a student-led event, the 1st student symposium by the UK Regional Student Group of the International Society for Computational Biology. The event took place on the 8th of October 2014.
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Affiliation(s)
- Farzana Rahman
- School of Computing and Mathematics, University of South Wales, Cardiff, CF37 1DL, UK
| | - Rohit Farmer
- School of Biosciences, University of Birmingham, UK, Birmingham, B15 2TT, UK
| | - Sayoni Das
- Research Department of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK
| | - Fatima Vayani
- Algorithms and Bioinformatics Group, King's College London, London, WC2R 2LS, UK
| | - Mehedi Hassan
- School of Computing and Mathematics, University of South Wales, Cardiff, CF37 1DL, UK
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