This chapter presents modelling gene regulatory networks (GRNs) using probabilistic causal model and the guided genetic algorithm. The problem of modelling is explained from both a biological and computational perspective. Further, a comprehensive methodology for developing a GRN model is pre-sented where the application of computation intelligence (CI) techniques can be seen to be significantly important in each phase of modelling. An illustrative example of the causal model for GRN modelling is also included and applied to model the yeast cell cycle dataset. The results obtained are compared for providing biological relevance to the findings which thereby underpins the CI based modelling techniques. © 2010, IGI Global.
|Title of host publication||Handbook of Research on Computational Methodologies in Gene Regulatory Networks|
|Editors||Sanjoy Das, Diona Caragea, Stephen M Welch, William H Hsu|
|Place of Publication||Hershey PA USA|
|Number of pages||21|
|Publication status||Published - 2009|