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Antimicrobial activity of methanolic extracts of Vernonia cinerea against Xanthomonas oryzae and identification of their compounds using in silico techniques. PLoS One 2021; 16:e0252759. [PMID: 34125862 PMCID: PMC8202908 DOI: 10.1371/journal.pone.0252759] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 05/22/2021] [Indexed: 12/25/2022] Open
Abstract
Bacterial Leaf Blight (BLB) disease is an extremely ruinous disease in rice, caused by Xanthomonas oryzae pv. oryzae (Xoo). Although various chemicals are available to manage BLB, they are toxic to the environment as well as humans. Hence there is a need to develop new pesticides as alternatives to hazardous chemicals. Therefore, a study was carried out to discover new potent natural pesticides against Xoo from different solvent extracts of Vernonia cinerea. Among all the fractions, the methanolic extract showed the highest inhibition zone. Further, to gain mechanistic insight of inhibitory action, 40 molecules of methanolic extracts were subjected for in silico study against two enzymes D-alanine—D-alanine ligase (Ddl) and Peptide deformylase (PDF). In silico study showed Rutin and Methanone, [1,4-dimethyl-7-(1- methylethyl)-2- azulenyl]phenyl have a good binding affinity with Ddl while Phenol, 2,4-bis(1-phenylethyl)- and 1,2-Benzenedicarboxylic acid, diisooctyl ester showed an excellent binding affinity to PDF. Finally, the system biology approach was applied to understand the agrochemical’s effect in the cell system of bacteria against both the enzymes. Conclusively, these four-hit compounds may have strong potential against Xoo and can be used as biopesticides in the future.
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Touré V, Dräger A, Luna A, Dogrusoz U, Rougny A. The Systems Biology Graphical Notation: Current Status and Applications in Systems Medicine. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11515-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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3
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Bhatt P, Sethi K, Gangola S, Bhandari G, Verma A, Adnan M, Singh Y, Chaube S. Modeling and simulation of atrazine biodegradation in bacteria and its effect in other living systems. J Biomol Struct Dyn 2020; 40:3285-3295. [PMID: 33179575 DOI: 10.1080/07391102.2020.1846623] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Atrazine is the most commonly used herbicide worldwide in the agricultural system. The increased environmental concentration of the atrazine showed the toxic effects on the non-target living species. Biodegradation of the atrazine is possible with the bacterial systems. The present study investigated biodegradation potential of atrazine degrading bacteria and the impact of atrazine on environmental systems. Model of atrazine fate in ecological systems constructed using the cell designer. The used model further analyzed and simulated to know the biochemistry and physiology of the atrazine in different cellular networks. Topological analysis of the atrazine degradation confirmed the 289 nodes and 300 edges. Our results showed that the overall biomagnification of the atrazine in the different environmental systems. Atrazine is showing toxic effects on humans and plants, whereas degraded by the bacterial systems. To date, no one has analyzed the complete degradation and poisonous effects of the atrazine in the environment. Therefore, this study is useful for overall system biology based modeling and simulation analysis of atrazine in living systems.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Pankaj Bhatt
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou, China.,Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Kanika Sethi
- Department of Microbiology, Dolphin (P.G) Institute of Biomedical and Natural Sciences, Dehradun, India
| | - Saurabh Gangola
- School of Agriculture, Graphic Era Hill University Bhimtal Campus, Uttarakhand, India
| | - Geeta Bhandari
- Department of Biotechnology, Sardar Bhagwan Singh University, Dehradun, Uttarakhand, India
| | - Amit Verma
- Department of Biochemistry, College of Basic Science and Humanities, SD Agricultural University, Gujarat, India
| | - Muhammad Adnan
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou, China.,Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Yashpal Singh
- Department of Veterinary Physiology and Biochemistry, G.B Pant University of Agriculture and Technology, Pantnagar, India
| | - Shshank Chaube
- Department of Mathematics, University of Petrolium and Energy Studies, Dehradun, India
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Bhatt K, Maheshwari DK. Insights into zinc-sensing metalloregulator 'Zur' deciphering mechanism of zinc transportation in Bacillus spp. by modeling, simulation and molecular docking. J Biomol Struct Dyn 2020; 40:764-779. [PMID: 32924811 DOI: 10.1080/07391102.2020.1818625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
To comprehend the molecular mechanism of zinc transportation by bacteria tends to be a very complicated and time-consuming method. To date, fragmented and scanty studies are available about the mechanism of zinc transportation at molecular level. So, the present study scrutinizes in silico pathways of zinc fractions transportation, specifically in Bacillus spp. stimulating dynamic performance of zinc. For this, the constructed model reveals Zur to be the prime regulatory transport protein maintaining bacterial survivability at fluctuation in zinc concentrations, thereby attaining zinc homeostasis. Topology for hub nodes displays appropriate evidence of the molecular basis of bacterial zinc imports and exports. Further, the molecular docking reveals interaction of Zur protein with the zinc ligands (ZnCO3 and ZnSO4). By validation of binding affinity, binding energy and docking score via Autodock Vina and X-Score, the ZnSO4 compound was found to possess excellent stability in the active pocket site of Zur, stating Zur-ZnSO4 complex to be the most potential. Owing to which, the Zur-ZnSO4 complex was selected and subjected to molecular dynamics simulation, revealing RMSD, RG, RMSF, SASA and interaction energy for 20 ns trajectory period. Henceforth,the study provides novel insight into revealing the unrecognized Zur protein pathway, assisting zinc transportation, besides retaining best interaction with ZnSO4 ligand. This is the first system biology where molecular docking and molecular dynamics simulation-based investigation decipher the role of Zur transport protein system and interaction of its amino acids with zinc ligands in a simpler and economical form via in silico techniques.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Kalpana Bhatt
- Department of Botany and Microbiology, Gurukula Kangri University, Haridwar, Uttarakhand, India
| | - Dinesh Kumar Maheshwari
- Department of Botany and Microbiology, Gurukula Kangri University, Haridwar, Uttarakhand, India
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5
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Beal J, Nguyen T, Gorochowski TE, Goñi-Moreno A, Scott-Brown J, McLaughlin JA, Madsen C, Aleritsch B, Bartley B, Bhakta S, Bissell M, Castillo Hair S, Clancy K, Luna A, Le Novère N, Palchick Z, Pocock M, Sauro H, Sexton JT, Tabor JJ, Voigt CA, Zundel Z, Myers C, Wipat A. Communicating Structure and Function in Synthetic Biology Diagrams. ACS Synth Biol 2019; 8:1818-1825. [PMID: 31348656 PMCID: PMC8023477 DOI: 10.1021/acssynbio.9b00139] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Biological engineers often find it useful to communicate using diagrams. These diagrams can include information both about the structure of the nucleic acid sequences they are engineering and about the functional relationships between features of these sequences and/or other molecular species. A number of conventions and practices have begun to emerge within synthetic biology for creating such diagrams, and the Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard to organize, systematize, and extend such conventions in order to produce a coherent visual language. Here, we describe SBOL Visual version 2, which expands previous diagram standards to include new functional interactions, categories of molecular species, support for families of glyph variants, and the ability to indicate modular structure and mappings between elements of a system. SBOL Visual 2 also clarifies a number of requirements and best practices, significantly expands the collection of glyphs available to describe genetic features, and can be readily applied using a wide variety of software tools, both general and bespoke.
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Affiliation(s)
- Jacob Beal
- BioCoder Consulting , Carlsbad 92008 , California , United States
- Raytheon BBN Technologies , Arlington , Virginia 22209 , United States
| | - Tramy Nguyen
- University of Utah , Salt Lake City , Utah 84112 , United States
| | | | | | | | | | - Curtis Madsen
- Boston University , Boston , Massachusetts 02215 , United States
| | | | - Bryan Bartley
- Raytheon BBN Technologies , Arlington , Virginia 22209 , United States
| | - Shyam Bhakta
- Rice University , Houston , Texas 77005 , United States
| | - Mike Bissell
- Amyris, Inc. , Emeryville , California 94608 , United States
| | | | - Kevin Clancy
- BioCoder Consulting , Carlsbad 92008 , California , United States
| | - Augustin Luna
- Harvard Medical School , Boston , Massachusetts 02115 , United States
| | | | - Zach Palchick
- Zymergen , Emeryville , California 94608 , United States
| | - Matthew Pocock
- Turing Ate My Hamster, Ltd. , Tyne And Wear NE27 0RT , U.K
| | - Herbert Sauro
- University of Washington , Seattle , Washington 98195 , United States
| | - John T Sexton
- Rice University , Houston , Texas 77005 , United States
| | | | | | - Zach Zundel
- University of Utah , Salt Lake City , Utah 84112 , United States
| | - Chris Myers
- University of Utah , Salt Lake City , Utah 84112 , United States
| | - Anil Wipat
- Newcastle University , Newcastle upon Tyne NE1 7RU , U.K
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6
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Pathak RK, Baunthiyal M, Pandey N, Pandey D, Kumar A. Modeling of the jasmonate signaling pathway in Arabidopsis thaliana with respect to pathophysiology of Alternaria blight in Brassica. Sci Rep 2017; 7:16790. [PMID: 29196636 PMCID: PMC5711873 DOI: 10.1038/s41598-017-16884-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 11/08/2017] [Indexed: 01/01/2023] Open
Abstract
The productivity of Oilseed Brassica, one of the economically important crops of India, is seriously affected by the disease, Alternaria blight. The disease is mainly caused by two major necrotrophic fungi, Alternaria brassicae and Alternaria brassicicola which are responsible for significant yield losses. Till date, no resistant source is available against Alternaria blight, hence plant breeding methods can not be used to develop disease resistant varieties. Jasmonate mediated signalling pathway, which is known to play crucial role during defense response against necrotrophs, could be strengthened in Brassica plants to combat the disease. Since scanty information is available in Brassica-Alternaria pathosystems at molecular level therefore, in the present study efforts have been made to model jasmonic acid pathway in Arabidopsis thaliana to simulate the dynamic behaviour of molecular species in the model. Besides, the developed model was also analyzed topologically for investigation of the hubs node. COI1 is identified as one of the promising candidate genes in response to Alternaria and other linked components of plant defense mechanisms against the pathogens. The findings from present study are therefore informative for understanding the molecular basis of pathophysiology and rational management of Alternaria blight for securing food and nutritional security.
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Affiliation(s)
- Rajesh Kumar Pathak
- Department of Biotechnology, Govind Ballabh Pant Institute of Engineering & Technology, Pauri Garhwal, 246194, Uttarakhand, India
| | - Mamta Baunthiyal
- Department of Biotechnology, Govind Ballabh Pant Institute of Engineering & Technology, Pauri Garhwal, 246194, Uttarakhand, India.
| | - Neetesh Pandey
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute (IASRI), Pusa, 110012, New Delhi, India
| | - Dinesh Pandey
- Department of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar, 263145, India
| | - Anil Kumar
- Department of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar, 263145, India.
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7
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Kawakami E, Singh VK, Matsubara K, Ishii T, Matsuoka Y, Hase T, Kulkarni P, Siddiqui K, Kodilkar J, Danve N, Subramanian I, Katoh M, Shimizu-Yoshida Y, Ghosh S, Jere A, Kitano H. Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways. NPJ Syst Biol Appl 2016; 2:15018. [PMID: 28725465 PMCID: PMC5516916 DOI: 10.1038/npjsba.2015.18] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Revised: 09/08/2015] [Accepted: 10/13/2015] [Indexed: 11/09/2022] Open
Abstract
Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker's or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow-tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow-tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems.
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Affiliation(s)
- Eiryo Kawakami
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan
| | | | | | - Takashi Ishii
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan
| | | | | | | | | | | | | | | | | | - Yuki Shimizu-Yoshida
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan.,Sony Computer Science Laboratories, Inc., Tokyo, Japan
| | | | - Abhay Jere
- LABS, Persistent Systems Limited, Pune, India
| | - Hiroaki Kitano
- Laboratory for Disease Systems Modeling, RIKEN-IMS, Kanagawa, Japan.,The Systems Biology Institute, Tokyo, Japan.,Sony Computer Science Laboratories, Inc., Tokyo, Japan.,Integrated Open Systems Unit, Okinawa Institute of Science and Technology, Okinawa, Japan
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8
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Deans RM, Taniguchi M, Chandrashaker V, Ptaszek M, Chambers DR, Soares ARM, Lindsey JS. Complexity in structure-directed prebiotic chemistry. Unexpected compositional richness from competing reactants in tetrapyrrole formation. NEW J CHEM 2016. [DOI: 10.1039/c6nj00543h] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Acyclic reactants afford “partially defective” pyrroles that interfere with chain growth of “normal” pyrroles on the path to tetrapyrrole macrocycles.
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Affiliation(s)
- Richard M. Deans
- Department of Chemistry
- North Carolina State University
- Raleigh
- USA
| | | | | | - Marcin Ptaszek
- Department of Chemistry
- North Carolina State University
- Raleigh
- USA
| | - Dana R. Chambers
- Department of Chemistry
- North Carolina State University
- Raleigh
- USA
| | - Ana R. M. Soares
- Department of Chemistry
- North Carolina State University
- Raleigh
- USA
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9
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Deans RM, Taniguchi M, Chandrashaker V, Ptaszek M, Lindsey JS. Complexity in structure-directed prebiotic chemistry. Reaction bifurcation from a β-diketone in tetrapyrrole formation. NEW J CHEM 2016. [DOI: 10.1039/c6nj00545d] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
An unsymmetrical β-diketone with δ-aminolevulinic acid affords both a “defective” and a “normal” pyrrole; upon combinatorial reaction the former terminates chain-growth of the latter on the path to tetrapyrrole macrocycles.
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Affiliation(s)
- Richard M. Deans
- Department of Chemistry
- North Carolina State University
- Raleigh
- USA
| | | | | | - Marcin Ptaszek
- Department of Chemistry
- North Carolina State University
- Raleigh
- USA
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10
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Matsuoka Y, Funahashi A, Ghosh S, Kitano H. Modeling and simulation using CellDesigner. Methods Mol Biol 2014; 1164:121-45. [PMID: 24927840 DOI: 10.1007/978-1-4939-0805-9_11] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In silico modeling and simulation are effective means to understand how the regulatory systems function in life. In this chapter, we explain how to build a model and run the simulation using CellDesigner, adopting the standards such as SBML and SBGN.
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Affiliation(s)
- Yukiko Matsuoka
- The Systems Biology Institute, 5-6-9 Shirokanedai, Minato-ku, Tokyo, 108-0071, Japan
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11
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Gupta MK, Misra K. Modeling and simulation analysis of propyl-thiouracil (PTU), an anti-thyroid drug on thyroid peroxidase (TPO), thyroid stimulating hormone receptor (TSHR), and sodium iodide (NIS) symporter based on systems biology approach. ACTA ACUST UNITED AC 2013. [DOI: 10.1007/s13721-013-0023-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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12
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A Calculus of Chemical Systems. IN SEARCH OF ELEGANCE IN THE THEORY AND PRACTICE OF COMPUTATION 2013. [DOI: 10.1007/978-3-642-41660-6_24] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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13
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Abstract
Background Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions The use of an established and well-known graphical language in the development of biomedical ontologies provides a more intuitive form of capturing and representing knowledge than using only text-based notations. The use of the profile requires the domain expert to reason about the underlying semantics of the concepts and relationships being modeled, which helps preventing the introduction of inconsistencies in an ontology under development and facilitates the identification and correction of errors in an already defined ontology.
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Affiliation(s)
- Gabriela D A Guardia
- Department of Computer Science and Mathematics, DCM/FFCLRP, University of Sao Paulo Av Bandeirantes, 3900 Monte Alegre Ribeirao Preto, SP 14040-901, Brazil.
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14
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Navas-Delgado I, Real-Chicharro A, Medina MA, Sanchez-Jimenez F, Aldana-Montes JF. Social pathway annotation: extensions of the systems biology metabolic modelling assistant. Brief Bioinform 2010; 12:576-87. [DOI: 10.1093/bib/bbq061] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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15
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Demir E, Cary MP, Paley S, Fukuda K, Lemer C, Vastrik I, Wu G, D'Eustachio P, Schaefer C, Luciano J, Schacherer F, Martinez-Flores I, Hu Z, Jimenez-Jacinto V, Joshi-Tope G, Kandasamy K, Lopez-Fuentes AC, Mi H, Pichler E, Rodchenkov I, Splendiani A, Tkachev S, Zucker J, Gopinath G, Rajasimha H, Ramakrishnan R, Shah I, Syed M, Anwar N, Babur O, Blinov M, Brauner E, Corwin D, Donaldson S, Gibbons F, Goldberg R, Hornbeck P, Luna A, Murray-Rust P, Neumann E, Ruebenacker O, Reubenacker O, Samwald M, van Iersel M, Wimalaratne S, Allen K, Braun B, Whirl-Carrillo M, Cheung KH, Dahlquist K, Finney A, Gillespie M, Glass E, Gong L, Haw R, Honig M, Hubaut O, Kane D, Krupa S, Kutmon M, Leonard J, Marks D, Merberg D, Petri V, Pico A, Ravenscroft D, Ren L, Shah N, Sunshine M, Tang R, Whaley R, Letovksy S, Buetow KH, Rzhetsky A, Schachter V, Sobral BS, Dogrusoz U, McWeeney S, Aladjem M, Birney E, Collado-Vides J, Goto S, Hucka M, Le Novère N, Maltsev N, Pandey A, Thomas P, Wingender E, Karp PD, Sander C, Bader GD. The BioPAX community standard for pathway data sharing. Nat Biotechnol 2010; 28:935-42. [PMID: 20829833 PMCID: PMC3001121 DOI: 10.1038/nbt.1666] [Citation(s) in RCA: 432] [Impact Index Per Article: 30.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.
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Affiliation(s)
- Emek Demir
- Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA
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16
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Russo C, Beaujois R, Bodart JF, Blossey R. Kicked by Mos and tuned by MPF-the initiation of the MAPK cascade in Xenopus oocytes. HFSP JOURNAL 2009; 3:428-40. [PMID: 20514133 DOI: 10.2976/1.3265771] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2009] [Accepted: 09/24/2009] [Indexed: 11/19/2022]
Abstract
The mitogen-activated protein kinase (MAPK) cascade is a paradigmatic signaling cascade, which plays a crucial role in many aspects of cellular events. The main initiator of the cascade in Xenopus oocytes is the oncoprotein Mos. After activation of the cascade, Mos activity is stabilized by MAPK via a feedback loop. Mos concentration levels are, however, not controlled by MAPK alone. In this paper we show, by imposing either a sustained or a peaked activity of M-phase promoting factor (MPF) (Cdc2-cyclin B), how the latter regulates the dynamics of Mos. Our experiments are supported by a detailed kinetic model for the Mos-MPF-MAPK network, which takes into account the three different phosphorylation states of Mos and, as a consequence, allows us to determine the time evolution of Mos under control of MPF. Our work opens a path toward a more complete and biologically realistic quantitative understanding of the dynamic interdependence of Mos and MPF in Xenopus oocytes.
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17
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Mi H, Thomas P. PANTHER pathway: an ontology-based pathway database coupled with data analysis tools. Methods Mol Biol 2009; 563:123-40. [PMID: 19597783 DOI: 10.1007/978-1-60761-175-2_7] [Citation(s) in RCA: 443] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The availability of whole genome sequences from various model organisms and increasing experimental data and literatures stimulated the evolution of a systems approach for biological research. The development of computational tools and algorithms to study biological pathway networks has made great progress in helping analyze research data. Pathway databases become an integral part of such an approach. This chapter first discusses how biological knowledge is represented, particularly the importance of ontologies or standards in systems biology research. Next, we use PANTHER Pathway as an example to illustrate how ontologies and standards play a role in data modeling, data entry, and data display. Last, we describe the usage of such systems. We also describe the computational tools that utilize PANTHER Pathway information to analyze gene expression experimental data.
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Affiliation(s)
- Huaiyu Mi
- Evolutionary Systems Biology Group, SRI International, Menlo Park, CA, USA
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18
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Le Novère N, Hucka M, Mi H, Moodie S, Schreiber F, Sorokin A, Demir E, Wegner K, Aladjem MI, Wimalaratne SM, Bergman FT, Gauges R, Ghazal P, Kawaji H, Li L, Matsuoka Y, Villéger A, Boyd SE, Calzone L, Courtot M, Dogrusoz U, Freeman TC, Funahashi A, Ghosh S, Jouraku A, Kim S, Kolpakov F, Luna A, Sahle S, Schmidt E, Watterson S, Wu G, Goryanin I, Kell DB, Sander C, Sauro H, Snoep JL, Kohn K, Kitano H. The Systems Biology Graphical Notation. Nat Biotechnol 2009; 27:735-41. [PMID: 19668183 DOI: 10.1038/nbt.1558] [Citation(s) in RCA: 534] [Impact Index Per Article: 35.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.
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Matsuoka Y, Ghosh S, Kitano H. Consistent design schematics for biological systems: standardization of representation in biological engineering. J R Soc Interface 2009; 6 Suppl 4:S393-404. [PMID: 19493898 PMCID: PMC2843967 DOI: 10.1098/rsif.2009.0046.focus] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2009] [Accepted: 05/05/2009] [Indexed: 11/12/2022] Open
Abstract
The discovery by design paradigm driving research in synthetic biology entails the engineering of de novo biological constructs with well-characterized input-output behaviours and interfaces. The construction of biological circuits requires iterative phases of design, simulation and assembly, leading to the fabrication of a biological device. In order to represent engineered models in a consistent visual format and further simulating them in silico, standardization of representation and model formalism is imperative. In this article, we review different efforts for standardization, particularly standards for graphical visualization and simulation/annotation schemata adopted in systems biology. We identify the importance of integrating the different standardization efforts and provide insights into potential avenues for developing a common framework for model visualization, simulation and sharing across various tools. We envision that such a synergistic approach would lead to the development of global, standardized schemata in biology, empowering deeper understanding of molecular mechanisms as well as engineering of novel biological systems.
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Heath LS, Sioson AA. Semantics of multimodal network models. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2009; 6:271-280. [PMID: 19407351 DOI: 10.1109/tcbb.2007.70242] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
A multimodal network (MMN) is a novel graph-theoretic formalism designed to capture the structure of biological networks and to represent relationships derived from multiple biological databases. MMNs generalize the standard notions of graphs and hypergraphs, which are the bases of current diagrammatic representations of biological phenomena, and incorporate the concept of mode. Each vertex of an MMN is a biological entity, a biot, while each modal hyperedge is a typed relationship, where the type is given by the mode of the hyperedge. The semantics of each modal hyperedge e is given through denotational semantics, where a valuation function fe defines the relationship among the values of the vertices incident on e. The meaning of an MMN is denoted in terms of the semantics of a hyperedge sequence. A companion paper defines MMNs and concentrates on the structural aspects of MMNs. This paper develops MMN denotational semantics when used as a representation of the semantics of biological networks and discusses applications of MMNs in managing complex biological data.
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Affiliation(s)
- Lenwood S Heath
- Department of Computer Science, Virginia Tech, Blacksburg, VA 24061-0106, USA.
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van Iersel MP, Kelder T, Pico AR, Hanspers K, Coort S, Conklin BR, Evelo C. Presenting and exploring biological pathways with PathVisio. BMC Bioinformatics 2008; 9:399. [PMID: 18817533 PMCID: PMC2569944 DOI: 10.1186/1471-2105-9-399] [Citation(s) in RCA: 247] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2008] [Accepted: 09/25/2008] [Indexed: 01/09/2023] Open
Abstract
Background Biological pathways are a useful abstraction of biological concepts, and software tools to deal with pathway diagrams can help biological research. PathVisio is a new visualization tool for biological pathways that mimics the popular GenMAPP tool with a completely new Java implementation that allows better integration with other open source projects. The GenMAPP MAPP file format is replaced by GPML, a new XML file format that provides seamless exchange of graphical pathway information among multiple programs. Results PathVisio can be combined with other bioinformatics tools to open up three possible uses: visual compilation of biological knowledge, interpretation of high-throughput expression datasets, and computational augmentation of pathways with interaction information. PathVisio is open source software and available at . Conclusion PathVisio is a graphical editor for biological pathways, with flexibility and ease of use as primary goals.
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Affiliation(s)
- Martijn P van Iersel
- Department of Bioinformatics, BiGCaT Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, the Netherlands.
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Abstract
UNLABELLED Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Matthew Suderman
- McGill Centre for Bioinformatics, 3775 University Street, Montreal, QCH3A 2B4, Canada.
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Kohn KW, Aladjem MI, Kim S, Weinstein JN, Pommier Y. Depicting combinatorial complexity with the molecular interaction map notation. Mol Syst Biol 2006; 2:51. [PMID: 17016517 PMCID: PMC1681518 DOI: 10.1038/msb4100088] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2006] [Accepted: 07/02/2006] [Indexed: 12/26/2022] Open
Abstract
To help us understand how bioregulatory networks operate, we need a standard notation for diagrams analogous to electronic circuit diagrams. Such diagrams must surmount the difficulties posed by complex patterns of protein modifications and multiprotein complexes. To meet that challenge, we have designed the molecular interaction map (MIM) notation (http://discover.nci.nih.gov/mim/). Here we show the advantages of the MIM notation for three important types of diagrams: (1) explicit diagrams that define specific pathway models for computer simulation; (2) heuristic maps that organize the available information about molecular interactions and encompass the possible processes or pathways; and (3) diagrams of combinatorially complex models. We focus on signaling from the epidermal growth factor receptor family (EGFR, ErbB), a network that reflects the major challenges of representing in a compact manner the combinatorial complexity of multimolecular complexes. By comparing MIMs with other diagrams of this network that have recently been published, we show the utility of the MIM notation. These comparisons may help cell and systems biologists adopt a graphical language that is unambiguous and generally understood.
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Affiliation(s)
- Kurt W Kohn
- Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA.
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Blinov ML, Yang J, Faeder JR, Hlavacek WS. Graph Theory for Rule-Based Modeling of Biochemical Networks. LECTURE NOTES IN COMPUTER SCIENCE 2006. [DOI: 10.1007/11905455_5] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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Kohn KW, Aladjem MI, Weinstein JN, Pommier Y. Molecular interaction maps of bioregulatory networks: a general rubric for systems biology. Mol Biol Cell 2005; 17:1-13. [PMID: 16267266 PMCID: PMC1345641 DOI: 10.1091/mbc.e05-09-0824] [Citation(s) in RCA: 75] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the molecular interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the molecular interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.
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Affiliation(s)
- Kurt W Kohn
- Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
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Kitano H, Funahashi A, Matsuoka Y, Oda K. Using process diagrams for the graphical representation of biological networks. Nat Biotechnol 2005; 23:961-6. [PMID: 16082367 DOI: 10.1038/nbt1111] [Citation(s) in RCA: 280] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
With the increased interest in understanding biological networks, such as protein-protein interaction networks and gene regulatory networks, methods for representing and communicating such networks in both human- and machine-readable form have become increasingly important. Although there has been significant progress in machine-readable representation of networks, as exemplified by the Systems Biology Mark-up Language (SBML) (http://www.sbml.org) issues in human-readable representation have been largely ignored. This article discusses human-readable diagrammatic representations and proposes a set of notations that enhances the formality and richness of the information represented. The process diagram is a fully state transition-based diagram that can be translated into machine-readable forms such as SBML in a straightforward way. It is supported by CellDesigner, a diagrammatic network editing software (http://www.celldesigner.org/), and has been used to represent a variety of networks of various sizes (from only a few components to several hundred components).
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Affiliation(s)
- Hiroaki Kitano
- The Systems Biology Institute, Suite 6A, M31 6-31-15 Jingumae, Shibuya, Tokyo, 150-0001 Japan.
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Cummings A, Kavlock R. A systems biology approach to developmental toxicology. Reprod Toxicol 2005; 19:281-90. [PMID: 15686864 DOI: 10.1016/j.reprotox.2004.10.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2004] [Revised: 09/17/2004] [Accepted: 10/09/2004] [Indexed: 11/24/2022]
Abstract
Recent advances in developmental biology have yielded detailed models of gene regulatory networks (GRNs) involved in cell specification and other processes in embryonic differentiation. Such networks form the bedrock on which a systems biology approach to developmental toxicology can be built. In this review, an introduction to GRNs in general is followed by a description of specific networks involved in sea urchin and Drosophila development. A hypothesis is presented regarding the role of GRN analysis in the determination of mechanisms of chemical toxicity during embryonic development. Potential for future directions and research approaches in this area is discussed.
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Affiliation(s)
- Audrey Cummings
- Reproductive Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
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Oda K, Matsuoka Y, Funahashi A, Kitano H. A comprehensive pathway map of epidermal growth factor receptor signaling. Mol Syst Biol 2005; 1:2005.0010. [PMID: 16729045 PMCID: PMC1681468 DOI: 10.1038/msb4100014] [Citation(s) in RCA: 697] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2005] [Accepted: 04/28/2005] [Indexed: 11/09/2022] Open
Abstract
The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML).
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Affiliation(s)
- Kanae Oda
- The Systems Biology Institute, Tokyo, Japan
- Department of Fundamental Science and Technology, Keio University, Tokyo, Japan
| | - Yukiko Matsuoka
- The Systems Biology Institute, Tokyo, Japan
- ERATO-SORST Kitano Symbiotic Systems Project, Japan Science and Technology Agency, Tokyo, Japan
| | - Akira Funahashi
- The Systems Biology Institute, Tokyo, Japan
- ERATO-SORST Kitano Symbiotic Systems Project, Japan Science and Technology Agency, Tokyo, Japan
| | - Hiroaki Kitano
- The Systems Biology Institute, Tokyo, Japan
- Department of Fundamental Science and Technology, Keio University, Tokyo, Japan
- ERATO-SORST Kitano Symbiotic Systems Project, Japan Science and Technology Agency, Tokyo, Japan
- Sony Computer Science Laboratories, Inc., Tokyo, Japan
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Abstract
MOTIVATION Visualization is indispensable in the research of complex biochemical networks. Available graph layout algorithms are not adequate for satisfactorily drawing such networks. New methods are required to visualize automatically the topological architectures and facilitate the understanding of the functions of the networks. RESULTS We propose a novel layout algorithm to draw complex biochemical networks. A network is modeled as a system of interacting nodes on squared grids. A discrete cost function between each node pair is designed based on the topological relation and the geometric positions of the two nodes. The layouts are produced by minimizing the total cost. We design a fast algorithm to minimize the discrete cost function, by which candidate layouts can be produced efficiently. A simulated annealing procedure is used to choose better candidates. Our algorithm demonstrates its ability to exhibit cluster structures clearly in relatively compact layout areas without any prior knowledge. We developed Windows software to implement the algorithm for CADLIVE. AVAILABILITY All materials can be freely downloaded from http://kurata21.bio.kyutech.ac.jp/grid/grid_layout.htm; http://www.cadlive.jp/ SUPPLEMENTARY INFORMATION http://kurata21.bio.kyutech.ac.jp/grid/grid_layout.htm; http://www.cadlive.jp/
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Affiliation(s)
- Weijiang Li
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka, Japan
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Abstract
The metabolic syndrome is a highly complex breakdown of normal physiology characterized by obesity, insulin resistance, hyperlipidemia, and hypertension. Type 2 diabetes is a major manifestation of this syndrome, although increased risk for cardiovascular disease (CVD) often precedes the onset of frank clinical diabetes. Prevention and cure for this disease constellation is of major importance to world health. Because the metabolic syndrome affects multiple interacting organ systems (i.e., it is a systemic disease), a systems-level analysis of disease evolution is essential for both complete elucidation of its pathophysiology and improved approaches to therapy. The goal of this review is to provide a perspective on systems-level approaches to metabolic syndrome, with particular emphasis on type 2 diabetes. We consider that metabolic syndromes take over inherent dynamics of our body that ensure robustness against unstable food supply and pathogenic infections, and lead to chronic inflammation that ultimately results in CVD. This exemplifies how trade-offs between robustness against common perturbations (unstable food and infections) and fragility against unusual perturbations (high-energy content foods and low-energy utilization lifestyle) is exploited to form chronic diseases. Possible therapeutic approaches that target fragility of emergent robustness of the disease state have been discussed. A detailed molecular interaction map for adipocyte, hepatocyte, skeletal muscle cell, and pancreatic beta-cell cross-talk in the metabolic syndrome can be viewed at http://www.systems-biology.org/001/003.html.
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Affiliation(s)
- Hiroaki Kitano
- Sony Computer Science Laboratories, Inc. 3-14-13, Higashi-Gotanda, Shinagawa, Tokyo 141-0022 Japan.
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Abstract
Cellular regulation comprises overwhelmingly complex interactions between genes and proteins that ultimately will only be rendered understandable by employing formal approaches. Developing large-scale mathematical models of such systems in an efficient and reliable way, however, requires careful evaluation of structuring principles for the models, of the description of the system dynamics, and of the experimental data basis for adjusting the models to reality. We discuss these three aspects of model development using the example of cell cycle regulation in yeast and suggest that capturing complex dynamic networks is feasible despite incomplete (quantitative) biological knowledge.
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Affiliation(s)
- Jörg Stelling
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg 39106, Germany.
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Aladjem MI, Pasa S, Parodi S, Weinstein JN, Pommier Y, Kohn KW. Molecular interaction maps--a diagrammatic graphical language for bioregulatory networks. Sci Signal 2004; 2004:pe8. [PMID: 14997004 DOI: 10.1126/stke.2222004pe8] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Molecular interaction maps (MIMs) use a clear, accurate, and versatile graphical language to depict complex biological processes. Here, we discuss the main features of the MIM language and its potential uses. MIMs can be used as database resources and simulation guides, and can serve to generate new hypotheses regarding the roles of specific molecules in the bioregulatory networks that control progression through the cell cycle, differentiation, and cell death.
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Affiliation(s)
- Mirit I Aladjem
- Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
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