The genome projects have provided comprehensive information about the basic building blocks of life. The next challenge is to understand how biological functions emerge from complex interactions of these building blocks. In this work, we present a generic, extensible in silico simulation framework which allows the experimenter to lest various hypotheses of an experiment 'in silico' and develop a model for subsequent wet test analysis. Undertaking a systems approach, we abstract a biological process as a set of interacting functions driven in time by a set of discrete events. We focus on three two-component gene regulatory networks, (a) PhoP/PhoQ network (b) barA/sirA network and (c) pmrB/pmrA network involved in bacterial pathogenesis in Salmonella Typhimurium and capture their interactions in various stages of infection. We report results on the expression of various gene and gene products from these pathways. We conclude that such a stochastic framework can provide insight into how collective interaction of different molecules manifests in physiology and diseases.
['Samik Ghosh', 'Preetam Ghosh', 'Kalyan Basu', 'Sajal K. Das']
iSimBioSys: an 'in silico' discrete event simulation framework for modeling biological systems