A New Approach for Modelling Gene Regulatory Networks Using Fuzzy Petri Nets

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doi doi:10.2390/biecoll-jib-2010-113
submission December 04, 2009
published February 04, 2010
NCBI PubMed PubMed ID 20134077

Raed I Hamed, S I Ahson and R Parveen

Correspondence should be addressed to:
Raed Hamed
Department of Computer Science, JMI University, New Delhi-110025, India
moc.liamg@nullfni.dear


Abstract

Gene Regulatory Networks are models of genes and gene interactions at the expression level. The advent of microarray technology has challenged computer scientists to develop better algorithms for modeling the underlying regulatory relationship in between the genes. Fuzzy system has an ability to search microarray datasets for activator/repressor regulatory relationship. In this paper, we present a fuzzy reasoning model based on the Fuzzy Petri Net. The model considers the regulatory triplets by means of predicting changes in expression level of the target based on input expression level. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. Through formalization of fuzzy reasoning, we propose an approach to construct a rulebased reasoning system. The experimental results show the proposed approach is feasible and acceptable to predict changes in expression level of the target gene.

Reference

Raed I Hamed, S I Ahson and R Parveen. A New Approach for Modelling Gene Regulatory Networks Using Fuzzy Petri Nets. Journal of Integrative Bioinformatics, 7(1):113, 2010. Online Journal: http://journal.imbio.de/index.php?paper_id=113
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