New Applications of Soft

Computing in Bioinformatics:

A Review

  Amit Gaurav¹, Vivek Kumar² and Dr. Darshika Nigam^3,*

¹Galgotias College of Engg. & Tech., Greater Noida (UP)

 ²Delhi College of Tech. & Mnagment, Palwal, Haryana

^3,*Deptt. of Biochemistry, SLS Dr. B.R. Ambedker University, Agra (UP)

Bioinformatics is a promising and innovative research field. Soft Computing is playing a crucial role as it provides techniques that are especially well suited to obtain results in an efficient way and with a good level of quality. Soft Computing can also be useful to model the imprecision and uncertainty that the Bioinformatics data and problems have. In this paper, we survey the role of different soft computing paradigms, like Fuzzy Sets (FSs), Artificial Neural Networks (ANNs), evolutionary computation, Rough Sets (RSs), and Support Vector Machines (SVMs), biologically inspired algorithm like ant colony system, swarm intelligence and others in bioinformatics systems and problems.  In broader view the present review reveals the major process and functions which are handled by these computing techniques are pattern-recognition and data-mining tasks, clustering, classification, feature selection, and rule generation of Genomic sequence, protein structure, gene expression microarrays, and gene regulatory networks.

Keywords: Bioinformatics, Soft computing paradigm, Fuzzy sets, Artificial neural network, Rough sets, Support vector Machines, Ant colony system.

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