Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers.This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter.
Basic Principles and Features of Soft Computing and Bioinformatics: Bioinformatics: Tasks and Challenges; Soft Computing: Tools and Techniques; Biological Sequence Analysis: Combining Hidden Markov Model and Artificial Neural Networks for DNA Sequencing; Multiple Sequence Alignment Using Tabu Search and Genetic Algorithms; Molecular Structure Prediction and Drug Design: Protein Folding with Multi-Objective Evolutionary Algorithms and Neural Networks; In Silico Drug Design Using Evolutionary Approach; Clustering and Classification Tasks in Bioinformatics: Clustering of Microarray Data: Pattern Recognition and Soft Computing Approach; Soft Computing Techniques for Protein Classification; and other papers.