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Sci. STKE, 10 February 2004 PROTOCOLSDeveloping Complex Signaling Models Using GENESIS/KinetikitSharat Jacob Vayttaden* and Upinder Singh Bhalla* National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bangalore 560065, India. Abstract: The development of biologically realistic models of signaling pathways is a demanding process, involving computational challenges as well as those arising from the complexity of detailed pathway models. We have developed the General Neural Simulation System (GENESIS) and Kinetikit (GENESIS/Kinetikit), a graphical simulation environment for modeling biochemical signaling pathways using deterministic and stochastic methods. A library of models of several common signaling pathways complements the software. This combination of numerical computation engines, graphical modeling tools, and library of models is designed to build on the cumulative development of models and techniques from many sources. The complete simulation environment and demonstration models are available from (http://stke.sciencemag.org/cgi/content/full/sigtrans;2004/219/pl4/DC1; also at http://www.ncbs.res.in/~bhalla/kkit/download.html). The associated library of signaling pathways is based on published experimental and simulation studies and is curated to ensure that the simulation outcomes match published results. Models in the library are maintained in a database (http://doqcs.ncbs.res.in). Individual pathway models can be combined to build complex signaling network simulations. The overall goal of this process is to attain sufficient biological realism in models to directly compare their outcomes with experiments and to improve our understanding of complex signaling. *Corresponding authors. Telephone, +91-80-2363-6420; fax, +91-80-2363-6662; e-mail, sharat{at}ncbs.res.in; bhalla{at}ncbs.res.in
Citation: S. J. Vayttaden, U. S. Bhalla, Developing Complex Signaling Models Using GENESIS/Kinetikit. Sci. STKE 2004, pl4 (2004). The editors suggest the following Related Resources on Science sites:In Science Signaling
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Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882