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What is Causal Model

Chapter 10
Handbook of Research on Computational Methodologies in Gene Regulatory Networks
Bayesian model specifying direct and indirect cause and effect relationships amongst the variables.
Published in Chapter:
Modelling Gene Regulatory Networks Using Computational Intelligence Techniques
Ramesh Ram (Monash University, Australia) and Madhu Chetty (Monash University, Australia)
Copyright: © 2010 |Pages: 22
DOI: 10.4018/978-1-60566-685-3.ch010
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.
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