Modelling gene regulatory networks using computational intelligence techniques

Ramesh Ram; Madhusudan Rajgopal Chetty

doi:10.4018/978-1-60566-685-3.ch010

Modelling gene regulatory networks using computational intelligence techniques

Ramesh Ram, Madhusudan Rajgopal Chetty

Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Research › peer-review

1 Citation (Scopus)

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 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.

Original language	English
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
Publisher	IGI Global
Pages	244-264
Number of pages	21
Edition	1
ISBN (Print)	9781605666853
DOIs	https://doi.org/10.4018/978-1-60566-685-3.ch010
Publication status	Published - 2009

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10.4018/978-1-60566-685-3.ch010

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Cite this

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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 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. {\textcopyright} 2010, IGI Global.",

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Modelling gene regulatory networks using computational intelligence techniques. / Ram, Ramesh; Chetty, Madhusudan Rajgopal.

Handbook of Research on Computational Methodologies in Gene Regulatory Networks. ed. / Sanjoy Das; Diona Caragea; Stephen M Welch; William H Hsu. 1. ed. Hershey PA USA : IGI Global, 2009. p. 244-264.

Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Research › peer-review

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