Abstract
Modeling biological systems to understand their mechanistic behavior is an important activity in molecular systems biology. Mathematical modeling typically requires deep mathematical or computing knowledge, and this limits the spread of modeling tools among biologists. Graphical modeling languages have been introduced to minimize this limit. Here, we survey the main graphical formalisms (supported by software tools) available to model biological systems with a primary focus on their usability, within the framework of modeling reaction pathways with two-dimensional (2D) (possibly nested) compartments. Considering the main characteristics of the surveyed formalisms, we synthesise a new proposal (Style) and report the results of an online survey conducted among biologists to assess usability of available graphical formalisms. We consider this proposal a guideline developed from what we learned in the survey, which can inform development of graphical formalisms to model reaction pathways in 2D space.
- Ozgur E, Akman, David A. Rand, Paul E. Brown, and Andrew J. Millar. 2010. Robustness from flexibility in the fungal circadian clock. BMC Systems Biology 4, 1 (2010), 88.Google ScholarCross Ref
- B. Alberts. 2008. Molecular Biology of the Cell: Reference Edition. Number v. 1 in Molecular Biology of the Cell: Reference Edition. Taylor & Francis.Google Scholar
- Boanerges Aleman-Meza, Yihai Yu, Heinz-Bernd Schüttler, Jonathan Arnold, and Thiab R. Taha. 2009. KINSOLVER: A simulator for computing large ensembles of biochemical and gene regulatory networks. Computers & Mathematics with Applications 57, 3 (2009), 420--435. Google ScholarDigital Library
- Steven S. Andrews, Nathan J. Addy, Roger Brent, and Adam P. Arkin. 2010. Detailed simulations of cell biology with Smoldyn 2.1. PLoS Computational Biology 6, 3 (2010), e1000705.Google ScholarCross Ref
- John A. Bachman and Peter Sorger. 2011. New approaches to modeling complex biochemistry. Nature Methods 8, 2 (2011), 130.Google ScholarCross Ref
- Frank T. Bergmann and Herbert M. Sauro. 2006. SBW-a modular framework for systems biology. In Proceedings of the 38th Conference on Winter Simulation. Winter Simulation Conference, 1637--1645. Google ScholarDigital Library
- William J. Bosl. 2007. Systems biology by the rules: Hybrid intelligent systems for pathway modeling and discovery. BMC Systems Biology 1, 1 (2007), 13.Google ScholarCross Ref
- Dennis Bray, Robert B. Bourret, and Melvin I. Simon. 1993. Computer simulation of the phosphorylation cascade controlling bacterial chemotaxis. Molecular Biology of the Cell 4, 5 (1993), 469.Google ScholarCross Ref
- Henri Casanova, Thomas M. Bartol, Joel Stiles, and Francine Berman. 2001. Distributing MCell simulations on the Grid. International Journal of High Performance Computing Applications 15, 3 (2001), 243--257. Google ScholarDigital Library
- Deepak Chandran, Frank T. Bergmann, Herbert M. Sauro, and others. 2009. TinkerCell: Modular CAD tool for synthetic biology. Journal of Biological Engineering 3, 1 (2009), 19.Google ScholarCross Ref
- R. Cheong, A. Hoffmann, and A. Levchenko. 2008. Understanding NF-κ B signaling via mathematical modeling. Molecular Systems Biology 4, 192 (2008).Google Scholar
- Federica Ciocchetta, Adam Duguid, Stephen Gilmore, Maria Luisa Guerriero, and Jane Hillston. 2009. The Bio-PEPA tool suite. In Proceedings of the 6th International Conference on the Quantitative Evaluation of Systems (QEST ’09). IEEE, 309--310. Google ScholarDigital Library
- Robert Clewley. 2012. Hybrid models and biological model reduction with PyDSTool. PLoS Computational Biology 8, 8 (2012), e1002628.Google ScholarCross Ref
- Andy Cockburn, Amy Karlson, and Benjamin B. Bederson. 2008. A review of overview + detail, zooming, and focus + context interfaces. ACM Computing Surveys (CSUR) 41, 1 (2008), 2. Google ScholarDigital Library
- J. Colvin, M. I. Monine, J. R. Faeder, W. S. Hlavacek, D. D. Von Hoff, and R. G. Posner. 2009. Simulation of large-scale rule-based models. Bioinformatics 25, 7 (Apr 2009), 910--917. Google ScholarDigital Library
- L. Dematté, C. Priami, and A. Romanel. 2008. The Beta Workbench: A computational tool to study the dynamics of biological systems. Briefings in Bioinformatics 9, 5 (2008), 437--449.Google ScholarCross Ref
- Pawan Dhar, Tan Chee Meng, Sandeep Somani, Li Ye, Anand Sairam, Mandar Chitre, Zhu Hao, and Kishore Sakharkar. 2004. Cellware: A multi-algorithmic software for computational systems biology. Bioinformatics 20, 8 (2004), 1319--1321. Google ScholarDigital Library
- Niraj Dudani, Subhasis Ray, Siji George, and Upinder S. Bhalla. 2009. Multiscale modeling and interoperability in MOOSE. Neuroscience 10, Suppl 1 (2009), 54.Google Scholar
- Peter Eades, Wei Lai, Kazuo Misue, and Kozo Sugiyama. 1991. Preserving the Mental Map of a Diagram. International Institute for Advanced Study of Social Information Science, Fujitsu Limited.Google Scholar
- Florian Erhard, Caroline C. Friedel, and Ralf Zimmer. 2008. FERN--A Java framework for stochastic simulation and evaluation of reaction networks. BMC Bioinformatics 9, 1 (2008), 356.Google ScholarCross Ref
- Rudolf Fleischer and Colin Hirsch. 2001. Graph drawing and its applications. In Drawing Graphs. M. Kaufmann and D. Wagner, Eds., Springer, 1--22. Google ScholarDigital Library
- Yaniv Frishman and Ayellet Tal. 2004. Dynamic drawing of clustered graphs. In Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on. IEEE, 191--198. Google ScholarDigital Library
- Akira Funahashi, Yukiko Matsuoka, Akiya Jouraku, Mineo Morohashi, Norihiro Kikuchi, and Hiroaki Kitano. 2008. CellDesigner 3.5: A versatile modeling tool for biochemical networks. Proceedings of the IEEE 96, 8 (2008), 1254--1265.Google ScholarCross Ref
- T. D. Garvey, P. Lincoln, C. J. Pedersen, D. Martin, and M. Johnson. 2003. BioSPICE: Access to the most current computational tools for biologists. OMICS 7, 4 (2003), 411--420.Google ScholarCross Ref
- Nail M. Gizzatkulov, Igor I. Goryanin, Eugeny A. Metelkin, Ekaterina A. Mogilevskaya, Kirill V. Peskov, and Oleg V. Demin. 2010. DBSolve Optimum: A software package for kinetic modeling which allows dynamic visualization of simulation results. BMC Systems Biology 4, 1 (2010), 109.Google ScholarCross Ref
- Gerd Grünert and Peter Dittrich. 2011. Using the SRSim software for spatial and rule-based modeling of combinatorially complex biochemical reaction systems. In Membrane Computing. M. Gheorghe, T. Hinze, G. Paun, G. Rozenberg, and A. Salomaa, Eds., Springer, 240--256. Google ScholarDigital Library
- Anthony D. Hill, Jonathan R. Tomshine, Emma M. B. Weeding, Vassilios Sotiropoulos, and Yiannis N. Kaznessis. 2008. SynBioSS: The synthetic biology modeling suite. Bioinformatics 24, 21 (2008), 2551--2553. Google ScholarDigital Library
- S. Hoops, S. Sahle, R. Gauges, C. Lee, J. Pahle, N. Simus, M. Singhal, L. Xu, P. Mendes, and U. Kummer. 2006. COPASI--A COmplex PAthway SImulator. Bioinformatics 22, 24 (Dec 2006), 3067--3074. Google ScholarDigital Library
- Xiaodi Huang, Wei Lai, A. S. M. Sajeev, and Junbin Gao. 2007. A new algorithm for removing node overlapping in graph visualization. Information Sciences 177, 14 (2007), 2821--2844. Google ScholarDigital Library
- Michael Hucka, Andrew Finney, Herbert M. Sauro, Hamid Bolouri, John C. Doyle, Hiroaki Kitano, Adam P. Arkin, Benjamin J. Bornstein, Dennis Bray, Athel Cornish-Bowden, and others. 2003. The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics 19, 4 (2003), 524--531.Google ScholarCross Ref
- Jonathan R. Karr, Jayodita C. Sanghvi, Derek N. Macklin, Miriam V. Gutschow, Jared M. Jacobs, Benjamin Bolival Jr., Nacyra Assad-Garcia, John I. Glass, and Markus W. Covert. 2012. A whole-cell computational model predicts phenotype from genotype. Cell 150, 2 (2012), 389--401.Google ScholarCross Ref
- Boris N. Kholodenko. 2006. Cell-signalling dynamics in time and space. Nature Reviews Molecular Cell Biology 7 (2006), 165--176.Google ScholarCross Ref
- Andrzej M. Kierzek. 2002. STOCKS: STOChastic kinetic simulations of biochemical systems with Gillespie algorithm. Bioinformatics 18, 3 (2002), 470--481.Google ScholarCross Ref
- Hiroaki Kitano. 2002. Systems biology: A brief overview. Science 295, 5560 (2002), 1662--1664.Google Scholar
- F. Kolpakov, M. Puzanov, and A. Koshukov. 2006. BioUML: Visual modeling, automated code generation and simulation of biological systems. In Proceedings of the 5th International Conference on Bioinformatics of Genome Regulation and Structure. 281--285.Google Scholar
- Markus Koschorreck and Ernst D. Gilles. 2008. ALC: Automated reduction of rule-based models. BMC Systems Biology 2, 1 (2008), 91.Google ScholarCross Ref
- J. Krumsiek, S. Polsterl, D. M. Wittmann, and F. J. Theis. 2010. Odefy--from discrete to continuous models. BMC Bioinformatics 11 (2010), 233.Google ScholarCross Ref
- Hiroyuki Kurata, Kentaro Inoue, Kazuhiro Maeda, Koichi Masaki, Yuki Shimokawa, and Quanyu Zhao. 2007. Extended CADLIVE: A novel graphical notation for design of biochemical network maps and computational pathway analysis. Nucleic Acids Research 35, 20 (2007), e134--e134.Google ScholarCross Ref
- N. Le Novère, M. Hucka, H. Mi, S. Moodie, F. Schreiber, A. Sorokin, E. Demir, K. Wegner, M. I. Aladjem, S. M. Wimalaratne, F. T. Bergman, R. Gauges, P. Ghazal, H. Kawaji, L. Li, Y. Matsuoka, A. Villéger, S. E. Boyd, L. Calzone, M. Courtot, U. Dogrusoz, T. C. Freeman, A. Funahashi, S. Ghosh, A. Jouraku, S. Kim, F. Kolpakov, A. Luna, S. Sahle, E. Schmidt, S. Watterson, G. Wu, I. Goryanin, D. B. Kell, C. Sander, H. Sauro, J. L. Snoep, K. Kohn, and H. Kitano. 2009. The systems biology graphical notation. Nature Biotechnology 27 (2009), 735--741.Google ScholarCross Ref
- Nicolas Le Novere and Thomas Simon Shimizu. 2001. STOCHSIM: Modelling of stochastic biomolecular processes. Bioinformatics 17, 6 (2001), 575--576.Google ScholarCross Ref
- Dong-Yup Lee, Choamun Yun, Ayoun Cho, Bo Kyeng Hou, Sunwon Park, and Sang Yup Lee. 2006. WebCell: A web-based environment for kinetic modeling and dynamic simulation of cellular networks. Bioinformatics 22, 9 (2006), 1150--1151. Google ScholarDigital Library
- W. J. Longabaugh. 2012. BioTapestry: A tool to visualize the dynamic properties of gene regulatory networks. Methods in Molecular Biology (Clifton, NJ) 786 (2012), 359.Google Scholar
- Carlos F. Lopez, Jeremy L. Muhlich, John A. Bachman, and Peter K. Sorger. 2013. Programming biological models in Python using PySB. Molecular Systems Biology 9, 1 (2013).Google Scholar
- Aneil Mallavarapu, Matthew Thomson, Benjamin Ullian, and Jeremy Gunawardena. 2007. Modular model building. arXiv preprint arXiv:0710.3421 (2007).Google Scholar
- Anthea Maton, David Lahart, Jean Hopkins, Maryanna Quon Warner, Susan Johnson, and Jill D. Wright. 1997. Cells: Building Blocks of Life. Pearson Prentice Hall.Google Scholar
- Martin Meier-Schellersheim, Xuehua Xu, Bastian Angermann, Eric J. Kunkel, Tian Jin, and Ronald N. Germain. 2006. Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method. PLoS Computational Biology 2, 7 (2006), e82.Google ScholarCross Ref
- Pedro Mendes. 1993. GEPASI: A software package for modelling the dynamics, steady states and control of biochemical and other systems. Computer Applications in the Biosciences: CABIOS 9, 5 (1993), 563--571.Google Scholar
- John A. Miller, Andrew F. Seila, and Xuewei Xiang. 2000. The JSIM web-based simulation environment. Future Generation Computer Systems 17, 2 (2000), 119--133. Google ScholarDigital Library
- Bud Mishra, Marco Antoniotti, Salvatore Paxia, and Nadia Ugel. 2005. Simpathica: A computational systems biology tool within the valis bioinformatics environment. Computational Systems Biology (2005).Google Scholar
- I. I. Moraru, J. C. Schaff, B. M. Slepchenko, M. L. Blinov, F. Morgan, A. Lakshminarayana, F. Gao, Y. Li, and L. M. Loew. 2008. Virtual cell modelling and simulation software environment. IET Systems Biology 2, 5 (2008), 352--362.Google ScholarCross Ref
- M. J. Morine, A. C. Tierney, B. van Ommen, H. Daniel, S. Toomey, I. M. F. Gjelstad, I. C. Gormley, P. Prez-Martinez, C. A. Drevon, J. L-pez-Miranda, and H. M. Roche. 2011. Transcriptomic coordination in the human metabolic network reveals links between n-3 fat intake, adipose tissue gene expression and metabolic health. PLoS Computational Biology 7, 11 (2011).Google Scholar
- Christoph Müssel, Martin Hopfensitz, and Hans A. Kestler. 2010. BoolNet: An R package for generation, reconstruction and analysis of Boolean networks. Bioinformatics 26, 10 (2010), 1378--1380.Google ScholarDigital Library
- C. J. Myers, N. Barker, K. Jones, H. Kuwahara, C. Madsen, and N. P. Nguyen. 2009. iBioSim: A tool for the analysis and design of genetic circuits. Bioinformatics 25, 21 (Nov 2009), 2848--2849. Google ScholarDigital Library
- Christopher R. Myers, Ryan N. Gutenkunst, and James P. Sethna. 2007. Python unleashed on systems biology. Computing in Science & Engineering 9, 3 (2007), 34--37. Google ScholarDigital Library
- Gabriele Neyer. 2001. Map labeling with application to graph drawing. In Drawing Graphs. M. Kaufmann and D. Wagner, Eds., Springer, 247--273. Google ScholarDigital Library
- Brett G. Olivier and Jacky L. Snoep. 2004. Web-based kinetic modelling using JWS Online. Bioinformatics 20, 13 (2004), 2143--2144. Google ScholarDigital Library
- Julien F. Ollivier, Vahid Shahrezaei, and Peter S. Swain. 2010. Scalable rule-based modelling of allosteric proteins and biochemical networks. PLoS Computational Biology 6, 11 (2010), e1000975.Google ScholarCross Ref
- Andrew Phillips. 2009. A visual process calculus for biology. Symbolic Systems Biology: Theory and Methods. Jones and Bartlett.Google Scholar
- Corrado Priami. 2009. Algorithmic systems biology. CACM 52, 5 (2009), 80--88. Google ScholarDigital Library
- C. Priami, A. Regev, E. Shapiro, and W. Silverman. 2001. Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Information Processing Letter 80 (2001), 25--31. Google ScholarDigital Library
- Helen C. Purchase, Jo-Anne Allder, and David Carrington. 2001. User preference of graph layout aesthetics: A UML study. In Graph Drawing. M. Kaufmann and D. Wagner, Eds., Springer, 5--18. Google ScholarDigital Library
- S. Ramsey, D. Orrell, and H. Bolouri. 2005. Dizzy: Stochastic simulation of large-scale genetic regulatory networks. Journal of Bioinformatics Computing Biology 3, 2 (Apr 2005), 415--436.Google Scholar
- P. Rangamani, A. Lipshtat, E. U. Azeloglu, R. C. Calizo, M. Hu, S. Ghassemi, J. Hone, S. Scarlata, S. R. Neves, and R. Iyengar. 2013. Decoding information in cell shape. Cell 154, 6 (2013), 1356--69.Google ScholarCross Ref
- Andre S. Ribeiro, Daniel A. Charlebois, and Jason Lloyd-Price. 2007. CellLine, a stochastic cell lineage simulator. Bioinformatics 23, 24 (2007), 3409--3411. Google ScholarDigital Library
- Andre S. Ribeiro and Jason Lloyd-Price. 2007. SGN Sim, a stochastic genetic networks simulator. Bioinformatics 23, 6 (2007), 777--779. Google ScholarDigital Library
- S. K. Sadiq, R. Guixa-Gonzalez, E. Dainese, M. Pastor, G. De Fabritiis, and J. Selent. 2013. Molecular modeling and simulation of membrane lipid-mediated effects on GPCRs. Current Medicinal Chemistry 20, 1 (2013), 22--38.Google ScholarCross Ref
- Purvi Saraiya, Chris North, and Karen Duca. 2005. Visualizing biological pathways: Requirements analysis, systems evaluation and research agenda. Information Visualization 4, 3 (June 2005), 191--205. DOI: http://dx.doi.org/10.1057/palgrave.ivs.9500102 Google ScholarDigital Library
- A. M. Smith, W. Xu, Y. Sun, J. R. Faeder, and G. E. Marai. 2012. RuleBender: Integrated modeling, simulation and visualization for rule-based intracellular biochemistry. BMC Bioinformatics 13 Suppl 8 (2012), S3.Google Scholar
- Marc T. Vass, Clifford A. Shaffer, Naren Ramakrishnan, Layne T. Watson, and John J. Tyson. 2006. The JigCell model builder: A spreadsheet interface for creating biochemical reaction network models. IEEE/ACM Transactions on Computational Biology and Bioinformatics on 3, 2 (2006), 155--164. Google ScholarDigital Library
- Michael Weber and Ekkart Kindler. 2003. The petri net kernel. Petri Net Technology for Communication-Based Systems (2003), 109--123.Google Scholar
- Katja Wegner, Johannes Knabe, Mark Robinson, Attila Egri-Nagy, Maria Schilstra, and Chrystopher Nehaniv. 2007. The NetBuilder’project: Development of a tool for constructing, simulating, evolving, and analysing complex regulatory networks. BMC Systems Biology 1, Suppl 1 (2007), P72.Google ScholarCross Ref
- Hans V. Westerhoff and Bernhard O. Palsson. 2004. The evolution of molecular biology into systems biology. Nature Biotechnology 22, 10 (2004), 1249--1252.Google ScholarCross Ref
- J. Zheng, D. Zhang, P. F. Przytycki, R. Zielinski, J. Capala, and T. M. Przytycka. 2010. SimBoolNet—a Cytoscape plugin for dynamic simulation of signaling networks. Bioinformatics 26, 1 (2010), 141--142. Google ScholarDigital Library
Index Terms
- Graphical Modeling Tools for Systems Biology
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