Computational modeling in biology requires sophisticated software tools. Precise communication and effective sharing of the models developed by researchers requires standard formats for storing, annotating, and exchanging models between software systems. Developing such standards is the driving vision behind the Systems Biology Markup Language (SBML) and several related efforts that we discuss in this chapter. At the same time, such standards are only enablers and ideally should be hidden “under the hood” of modeling environments that provide users with high-level, flexible facilities for working with computational models. As an example of the modern software systems available today, we discuss the Virtual Cell and illustrate its support for typical modeling activities in biology.
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References
Alm E and Arkin AP (2003) Biological networks. Curr Opin Struc Biol 13: 193–202
Arkin A (2001) Synthetic cell biology. Curr Opin Biotech 12: 638–644
Booch G, Jacobson I and Rumbaugh J (2000) OMG Unified Modeling Language Specification. Object Management Group, Inc. Needham, MA, USA
Bornstein BJ, Keating SM, Jouraku A and Hucka M (2008) LibSBML: An API library for SBML. Bioinformatics 24: 880–881
Bower JM and Beeman D (1995) The Book of GENESIS: Exploring Realistic Neural Models with the GEneral NEural SImulation System. Springer, Santa Clara, California
Bower JM and Bolouri H (2001) Computational Modeling of Genetic and Biochemical Networks. MIT Press, Cambridge, MA
Bower JM, Beeman D and Hucka M (2002) The GENESIS simulation system. In: Arbib MA (ed) The Handbook of Brain Theory and Neural Networks pp. 475–478. MIT Press, Cambridge, MA
Bray T, Paoli J and Sperberg-McQueen CM (1998) Extensible markup language (xml) 1.0 (w3c recommendation 10-february-1998). http://www. w3.org/TR/
Church GM (2005) From systems biology to synthetic biology. Mol Sys Biol 1, p. 1, doi:10.1038/msb4100007
Csete ME and Doyle JC (2002) Reverse engineering of biological complexity. Science 295: 1664–1669
Endy D and Brent R (2001) Modelling cellular behaviour. Nature 409: 391–395
Fall C, Marland ES, Wagner JM and Tyson JJ (2002) Computational Cell Biology. Springer, New York
Fraser SE and Harland RM (2000) The molecular metamorphosis of experimental embryology. Cell 100: 41–55
Hartwell LH, Hopfield JJ, Leibler S and Murray AW (1999) From molecular to modular cell biology. Nature 402: C47–C52
Hedley WJ, Nelson MR, Bullivant DP and Nielson PF (2001) A short introduction to CellML. Phil Trans R Soc A 359: 1073–1089
Hines ML and Carnevale NT (1997) The NEURON simulation environment. Neural Comput 9: 1179–1209
Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A, Cuellar AA, Dronov S, Gilles ED, Ginkel M, Gor V, Goryanin II, Hedley WJ, Hodgman TC, Hofmeyr J-H, Hunter PJ, Juty NS, Kasberger JL, Kremling A, Kummer U, Le Novère N, Loew LM, Lucio D, Mendes P, Minch E, Mjolsness ED, Nakayama Y, Nelson MR, Nielsen PF, Sakurada T, Schaff JC, Shapiro BE, Shimizu TS, Spence HD, Stelling J, Takahashi K, Tomita M, Wagner J and Wang J (2003) The Systems Biology Markup Language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics 19: 524–531
Hucka M, Finney A, Bornstein BJ, Keating SM, Shapiro BE, Matthews J, Kovitz BL, Schilstra MJ, Funahashi A, Doyle JC and Kitano H (2004) Evolving a lingua franca and associated software infrastructure for computational systems biology: The Systems Biology Markup Language (SBML) project. Sys Biol 1: 41–53
Jacobs I and Walsh N (2004) Architecture of the world wide web, volume one: W3c recommendation 15 December 2004. W3C. http://www.w3.org/ TR/webarch/
Le Novère N, Finney A, Hucka M, Bhalla US, Campagne F, Collado-Vides J, Crampin EJ, Halstead M, Klipp E, Mendes P, Nielsen P, Sauro H, Shapiro BE, Snoep JL, Spence HD and Wanner BL (2005) Minimum Information Requested in the Annotation of biochemical Models (MIRIAM). Nat Biotechnol 23: 1509–1515
Le Novère N, Bornstein BJ, Broicher A, Courtot M, Donizelli M, Dharuri H, Li L, Sauro HM, Schilstra MJ, Shapiro BE, Snoep JL and Hucka M (2006) Biomodels database: A free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Res 34: D689–D691
Lloyd CM, Halstead MD and Nielsen PF (2004) CellML: Its future, present and past. Prog Biophys Mol Biol 85: 433–450
McAdams HH and Arkin A (1999) It's a noisy business! Genetic regulation at the nanomolar scale. Trends Genet 15: 65–69
Moraru II, Schaff JC, Slepchenko BM, Blinov ML, Morgan F, Lakshminarayana A, Gao F, Li Y, Loew LM (2008) Virtual Cell modelling and simulation software environment. IET Sys Biol 2(5): 352–362
Noble D (2002) The rise of computational biology. Nat Rev Mol Cell Bio 3: 460–463
Olivier BG and Snoep JL (2004) Web-based kinetic modelling using JWS online. Bioinformatics 20: 2143–2144
Phair RD and Misteli T (2001) Kinetic modelling approaches to in vivo imaging. Nat Rev Mol Cell Bio 2: 898–907
Schulz M, Uhlendorf J, Klipp E and Liebermeister W (2006) SBMLmerge, a system for combining biochemical network models. Genome Inform 17: 62–71
Slepchenko BM, Schaff JC, Carson JH and Loew LM (2002) Computational cell biology: Spatiotemporal simulation of cellular events. Annu Rev Bioph Biom 31: 423–441
Slepchenko BM, Schaff JC, Macara I and Loew LM (2003) Quantitative cell biology with the virtual cell. Trends Cell Biol 13: 570–576
Snoep JL and Olivier BG (2003) JWS online cellular systems modeling and microbiology. Microbiology 149: 3045–3047
Tyson JJ, Chen K and Novak B (2001) Network dynamics and cell physiology. Nat Rev Mol Cell Biol 2: 908–916
Yi T-M, Huang Y, Simon MI and Doyle J (2000) Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc Natl Acad Sci USA 97: 4649–4653
Zerhouni E (2003) The NIH roadmap. Science 302: 63–64
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Hucka, M., Schaff, J. (2009). Trends and Tools for Modeling in Modern Biology. In: Laisk, A., Nedbal, L., Govindjee (eds) Photosynthesis in silico . Advances in Photosynthesis and Respiration, vol 29. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9237-4_1
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