Modelling Gene Regulatory Networks Using Computational Intelligence Techniques

View Sample PDF

Author(s): Ramesh Ram (Monash University, Australia)and Madhu Chetty (Monash University, Australia)
Copyright: 2010
Pages: 22
Source title: Handbook of Research on Computational Methodologies in Gene Regulatory Networks
Source Author(s)/Editor(s): Sanjoy Das (Kansas State University, USA), Doina Caragea (Kansas State University, USA), Stephen Welch (Kansas State University, USA)and William H. Hsu (Kansas State University, USA)
DOI: 10.4018/978-1-60566-685-3.ch010

Keywords: Biologically-Inspired Computing / Medical Information Science Reference / Medical Technologies / Medicine & Healthcare

Purchase

View Modelling Gene Regulatory Networks Using Computational Intelligence Techniques on the publisher's website for pricing and purchasing information.

Abstract

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 presented 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.

The IRMA Community

Research IRM

Modelling Gene Regulatory Networks Using Computational Intelligence Techniques

Purchase

Abstract

Related Content

IRMA Sponsors