DocumentCode :
798433
Title :
Genetic Networks and Soft Computing
Author :
Mitra, Sushmita ; Das, Ratan ; Hayashi, Yoichi
Author_Institution :
Machine Intell. Unit, Indian Stat. Inst., Kolkata, India
Volume :
8
Issue :
1
fYear :
2011
Firstpage :
94
Lastpage :
107
Abstract :
The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem. Such reverse engineering of genetic networks offers insight into cellular activity toward prediction of adverse effects of new drugs or possible identification of new drug targets. Tasks such as classification, clustering, and feature selection enable efficient mining of knowledge about gene interactions in the form of networks. It is known that biological data is prone to different kinds of noise and ambiguity. Soft computing tools, such as fuzzy sets, evolutionary strategies, and neurocomputing, have been found to be helpful in providing low-cost, acceptable solutions in the presence of various types of uncertainties. In this paper, we survey the role of these soft methodologies and their hybridizations, for the purpose of generating genetic networks.
Keywords :
bioinformatics; cellular biophysics; genetic engineering; genetics; molecular biophysics; molecular configurations; neural nets; bioinformatics; cellular process; fuzzy sets; gene regulatory networks; neurocomputing; soft computing tool; Biochemistry; Cellular networks; Computer networks; Data mining; Drugs; Fluids and secretions; Gene expression; Genetics; Information analysis; Reverse engineering; Gene regulatory networks; artificial neural networks; fuzzy sets.; gene expression; genetic algorithms; microarray; reverse engineering; Cluster Analysis; Computational Biology; Data Mining; Databases, Factual; Fuzzy Logic; Gene Expression Profiling; Gene Regulatory Networks; Neural Networks (Computer);
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2009.39
Filename :
4906987
Link To Document :
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