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Towards large scale models of biochemical networks

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SDBW03 - Advances in numerical and analytic approaches for the study of non-spatial stochastic dynamical systems in molecular biology

Co-authors: Jose Juan Tapia (University of Pittsburgh), John Sekar (University of Pittsburgh)

In this talk I will address some of the challenges faced in developing detailed models of biochemical networks, which encompass large numbers of interacting components. Although simpler coarse-grained models are often useful for gaining insight into biological mechanisms, such detailed models are necessary to understand how molecular components work in the network context and essential to developing the ability to manipulate such networks for practical benefits. The rule-based modeling (RBM) approach, in which biological molecules can be represented as structured objects whose interactions are governed by rules that describe their biochemical interactions, is the basis for addressing multiple scaling issues that arise in the development of large scale models. Currently available software tools for RBM , such as BioNetGen, Kappa, and Simmune, enable the specification and simulation of large scale models, and these tools are in widespread use by the modeling community. I will re view some of the developments that gave rise to those capabilities, and then I will describe our current efforts broaden the appeal of these tools as well as to better enable collaborative development of models through re-use of existing models and improving visual representations of models.

Related Links

  • - For more information about rule-based modeling tools described in this talk.

This talk is part of the Isaac Newton Institute Seminar Series series.

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