Includes bibliographical references and index.

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. Presents the application of evolutionary computations for fractal visualization of sequence data. Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. Examines the roles of efficient computational techniques in biology.