Ontologies for Dynamic Modeling of Genetics Regulatory Networks

A Genetic Regulatory Network (GRN) is a collection of DNA segments in a cell which interact with each other and with other substances in the cell, thereby governing the rates at which genes in the network are transcribed into mRNA. Dynamic modeling of GRN´s consists in modeling these networks in both space and time. It allows predicting the functional robustness of these networks against variations of internal and external parameters. Ontologies are powerful tools to make dynamic modeling of GRN´s. In this paper we propose an approach based on ontologies for dynamic modeling of GRN´s. We have experimented our approach on the ABC model of the flower development of Arabidopsis Thaliana plant. Our approach enables to cluster Arabidopsis Thaliana genes into functional entities (genes responsible for salt resistance and genes responsible for ultra violet rays resistance).