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.

Bioinformatics is the science of managing, mining, integrating, and interpreting information from biological data at the genomic, metabalomic, proteomic, phylogenetic, cellular, or whole organism levels. The need for bioinformatics tools and expertise has increased as genome sequencing projects have resulted in an exponential growth in complete and partial sequence databases. These and other projects require the development of new ways to interpret the flood of biological data that exists today and that is anticipated in the future. Data mining or knowledge discovery from data (KDD), in its most fundamental form, is to extract interesting, nontrivial, implicit, previously unknown and potentially useful information from data. With the substantial growth of biological data, KDD will play a significant role in analyzing the data and in solving emerging problems. The aim of this book is to introduce the reader to some of the best techniques for data mining in bioinformatics (BIOKDD) in the hope that the reader will build on them to make new discoveries on his or her own.