 | AUTOMATIC MODEL GENERATION FOR SIGNAL TRANSDUCTION WITH APPLICATIONS TO MAP-KINASE PATHWAYS
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| | Bruce E Shapiro1), Andre Levchenko2) and Eric Mjolsness1) |
| 1) Jet Propulsion Laboratory, California Institute of Technology
2) Division of Biology and Division of Engineering and Applied Science, California Institute of Technology |
| | We describe a general approach to automatic model generation in the description of dynamic regulatory networks. Several potential areas of application of this technique are outlined. We then describe how a particular implementation of this approach, Cellerator©, has been used to study the mitogen-activated protein kinase(MAPK) cascade. These signal transduction modules occur both in solution and when bound to a scaffold protein, and we have generalized the technique to include both types of module. We show that the results of simulations with the Cellerator©-created model are consistent with our previously published report, where an independently written model was developed. New results made possible by the use of Cellerator© are also presented. An important aspect of Cellerator operation-explicit output description at several steps during model generation-is emphasized. This design allows intervention and modification of the model “on the go” leading to both a more flexible of model description and a straightforward error correction mechanism. We also outline our future plans in Cellerator© development. |
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