Modeling a hox gene network in silico using a stochastic simulation algorithm.
The amount of molecular information that has been gathered about Hox cis-regulatory mechanisms allows us to take the next important step: integrating the results and constructing a higher-level model for the interaction and regulation of the Hox genes. Here, we present the results of our investigation into a cis-regulatory network for the early Hox genes. Instead of using conventional differential equation approaches for analyzing the system, we have adopted the use of a stochastic simulation algorithm (SSA) to model the network. The model allows us to track in detail the behavior of each component of a biochemical pathway and to produce computerized movies of the time evolution of the system that is a result of the dynamic interplay of these various components. The simulation is able to reproduce key features of the wild-type pattern of gene expression, and in silico experiments yield results similar to their corresponding in vivo experiments. This analysis shows the utility of using stochastic methods to model biochemical networks. In addition, the model has suggested several intriguing new results that are currently being investigated in vivo.
Kastner
Jason
J
Department of Applied and Computational Mathematics, California Institute of Technology, Pasadena 91125, USA. kastner@gg.caltech.edu
Solomon
Jerry
J
Fraser
Scott
S
D000465:Algorithms; D005801:Genes, Homeobox; D005809:Genes, Regulator