BMC Systems Biology | |
NetworkViewer: visualizing biochemical reaction networks with embedded rendering of molecular interaction rules | |
Martin Meier-Schellersheim2  Fengkai Zhang2  Bastian R Angermann2  Hsueh-Chien Cheng1  | |
[1] Department of Computer Science, University of Maryland, A.V. Williams Building, University of Maryland, 20742 College Park, USA;Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Building 4, 4 Memorial Drive, 20892 Bethesda, USA | |
关键词: Rule-based modeling; Cellular signaling; Protein reaction networks; User interface; Visualization; | |
Others : 864944 DOI : 10.1186/1752-0509-8-70 |
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received in 2014-03-04, accepted in 2014-06-05, 发布年份 2014 | |
【 摘 要 】
Background
Network representations of cell-biological signaling processes frequently contain large numbers of interacting molecular and multi-molecular components that can exist in, and switch between, multiple biochemical and/or structural states. In addition, the interaction categories (associations, dissociations and transformations) in such networks cannot satisfactorily be mapped onto simple arrows connecting pairs of components since their specifications involve information such as reaction rates and conditions with regard to the states of the interacting components. This leads to the challenge of having to reconcile competing objectives: providing a high-level overview without omitting relevant information, and showing interaction specifics while not overwhelming users with too much detail displayed simultaneously. This problem is typically addressed by splitting the information required to understand a reaction network model into several categories that are rendered separately through combinations of visualizations and/or textual and tabular elements, requiring modelers to consult several sources to obtain comprehensive insights into the underlying assumptions of the model.
Results
We report the development of an application, the Simmune NetworkViewer, that visualizes biochemical reaction networks using iconographic representations of protein interactions and the conditions under which the interactions take place using the same symbols that were used to specify the underlying model with the Simmune Modeler. This approach not only provides a coherent model representation but, moreover, following the principle of “overview first, zoom and filter, then details-on-demand,” can generate an overview visualization of the global network and, upon user request, presents more detailed views of local sub-networks and the underlying reaction rules for selected interactions. This visual integration of information would be difficult to achieve with static network representations or approaches that use scripted model specifications without offering simple but detailed symbolic representations of molecular interactions, their conditions and consequences in terms of biochemical modifications.
Conclusions
The Simmune NetworkViewer provides concise, yet comprehensive visualizations of reaction networks created in the Simmune framework. In the near future, by adopting the upcoming SBML standard for encoding multi-component, multi-state molecular complexes and their interactions as input, the NetworkViewer will, moreover, be able to offer such visualization for any rule-based model that can be exported to that standard.
【 授权许可】
2014 Cheng et al.; licensee BioMed Central Ltd.
【 预 览 】
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【 图 表 】
Figure 3.
【 参考文献 】
- [1]Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: a software environment for integrated models of biomolecular interaction networks . Genome Res 2003, 13(11):2498-2504.
- [2]Breitkreutz BJ, Stark C, Tyers M: Osprey: a network visualization system . Genome Biol 2003, 4(3):22. BioMed Central Full Text
- [3]Hu Z, Mellor J, Wu J, DeLisi C: VisANT: an online visualization and analysis tool for biological interaction data . BMC Bioinformatics 2004, 5(1):17. BioMed Central Full Text
- [4]Novère NL, 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, et al.: The systems biology graphical notation . Nat Biotechnol 2009, 27(8):735-741.
- [5]Kohn KW, Aladjem MI, Weinstein JN, Pommier Y: Molecular interaction maps of bioregulatory networks: a general rubric for systems biology . Mol Biol Cell 2006, 17(1):1-13.
- [6]Luna A, Karac EI, Sunshine M, Chang L, Nussinov R, Aladjem MI, Kohn KW: A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method . BMC Bioinformatics 2011, 12:167. BioMed Central Full Text
- [7]Faeder JR, Blinov ML, Hlavacek WS: Rule-based modeling of biochemical systems with, BioNetGen . In Systems Biology. Volume 500 . Edited by Maly IV. Totowa: Humana Press; 2009:113-167.
- [8]Meier-Schellersheim M, Fraser IDC, Klauschen F: Multiscale modeling for biologists . Wiley Interdiscip Rev Syst Biol Med 2009, 1(1):4-14.
- [9]Feret J, Danos V, Krivine J, Harmer R, Fontana W: Internal coarse-graining of molecular systems . Proc Natl Acad Sci USA 2009, 106(16):6453-6458.
- [10]Faeder JR, Blinov ML, Hlavacek WS: Graphical rule-based representation of signal-transduction networks . In Proceedings of ACM Symposium on Applied Computing. SAC ‘05 . New York: ACM; 2005:133-140.
- [11]Hu B, Fricke GM, Faeder JR, Posner RG, Hlavacek WS: GetBonNie for building, analyzing and sharing rule-based models . Bioinformatics 2009, 25(11):1457-1460.
- [12]Zhang F, Angermann BR, Meier-Schellersheim M: The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions . Bioinformatics 2013, 29(9):1229-1230.
- [13]Smith AM, Xu W, Sun Y, Faeder JR, Marai GE: RuleBender: integrated modeling, simulation and visualization for rule-based intracellular biochemistry . BMC Bioinformatics 2012, 13(Suppl 8):3. BioMed Central Full Text
- [14]Chylek LA, Hu B, Blinov ML, Emonet T, Faeder JR, Goldstein B, Gutenkunst RN, Haugh JM, Lipniacki T, Posner RG, Yang J, Hlavacek WS: Guidelines for visualizing and annotating rule-based models . Mol BioSyst 2011, 7(10):2779-2795.
- [15]Tiger C-F, Krause F, Cedersund G, Palmer R, Klipp E, Hohmann S, Kitano H, Krantz M: A framework for mapping, visualisation and automatic model creation of signal-transduction networks . Mol Syst Biol 2012, 8:578.
- [16]Meier-Schellersheim M, Xu X, Angermann B, Kunkel EJ, Jin T, Germain RN: Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method . PLoS Comput Biol 2006, 2(7):82.
- [17]Angermann BR, Klauschen F, Garcia AD, Prustel T, Zhang F, Germain RN, Meier-Schellersheim M: Computational modeling of cellular signaling processes embedded into dynamic spatial contexts . Nat Methods 2012, 9(3):283-289.
- [18]van Iersel MP, Villéger AC, Czauderna T, Boyd SE, Bergmann FT, Luna A, Demir E, Sorokin A, Dogrusoz U, Matsuoka Y, Funahashi A, Aladjem MI, Mi H, Moodie SL, Kitano H, Le Novère N, Schreiber F: Software support for SBGN maps: SBGN-ML and LibSBGN . Bioinformatics 2012, 28(15):2016-2021.
- [19]Kohn KW, Aladjem MI, Weinstein JN, Pommier Y: Network architecture of signaling from uncoupled helicase-polymerase to cell cycle checkpoints and trans-lesion DNA synthesis . Cell Cycle 2009, 8(14):2281-2299.
- [20]North S: Drawing graphs with NEATO . 2004. [http://ftp.graphviz.org/pdf/neatoguide.pdf webcite]
- [21]Ellson J, Gansner E, Koutsofios L, North SC, Woodhull G: Graphviz–open source graph drawing tools . In Graph Drawing. Lecture Notes in Computer Science . Edited by Mutzel P, Jünger M, Leipert S. Berlin Heidelberg: Springer; 2002:483-484.
- [22]Gansner ER, Koutsofios E, North SC, Vo K-P: A technique for drawing directed graphs . IEEE Trans on Softw Eng 1993, 19(3):214-230.
- [23]Hsieh M-y, Yang S, Raymond-Stinz MA, Edwards JS, Wilson BS: Spatio-temporal modeling of signaling protein recruitment to EGFR . BMC Syst Biol 2010, 4:57. BioMed Central Full Text
- [24]SBML3 Multi-state, Multi-component [http://sbml.org/Documents/Specifications/SBML_Level_3/Packages/Multistate_and_Multicomponent_Species_(multi) webcite]