AN ONTOLOGICAL MODEL FOR KNOWLEDGE REPRESENTATION OF THE GENETIC REGULATION NETWORKS

Challenges of contemporary molecular biology include the prediction of gene regulation and interaction in network, which proteins participate in the pathway. A great challenge of post-genomic biology is to understand how cellular phenomena arise from connectivity of genes and proteins. The study of genetic regulatory networks has received a major impetus from the recent development of experimental techniques allowing the measurement of gene expression patterns in a massively parallel way. This experimental progress allows a development of appropriate computer tools for the knowledge representation and modeling of gene regulation processes. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this paper an ontological model for the knowledge representation of the genetic regulation networks.