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Preface. <p>Contributors.</p> <p><b>PART 1 INTRODUCTION.</b></p> <p>1 Computational Intelligence: Foundations, Perspectives, and Recent Trends (<i>Swagatam Das, Ajith Abraham, and B. K. Panigrahi).</i></p> <p>2 Fundamentals of Pattern Analysis: A Brief Overview (<i>Basabi Chakraborty</i>).</p> <p>3 Biological Informatics: Data, Tools, and Applications (<i>Kevin Byron, Miguel Cervantes-Cervantes, and Jason T. L. Wang</i>).</p> <p><b>PART II SEQUENCE ANALYSIS.</b></p> <p>4 Promoter Recognition Using Neural Network Approaches (<i>T. Sobha Rani, S. Durga Bhavani, and S. Bapi Raju</i>).</p> <p>5 Predicting microRNA Prostate Cancer Target Genes (<i>Francesco Masulli, Stefano Rovetta, and Giuseppe Russo</i>).</p> <p><b>PART III STRUCTURE ANALYSIS.</b></p> <p>6 Structural Search in RNA Motif Databases (<i>Dongrong Wen and Jason T. L. Wang</i>).</p> <p>7 Kernels on Protein Structures (<i>Sourangshu Bhattacharya, Chiranjib Bhattacharyya, and Nagasuma R. Chandra</i>).</p> <p>8 Characterization of Conformational Patterns in Active and Inactive Forms of Kinases using Protein Blocks Approach (<i>G. Agarwal, D. C. Dinesh, N. Srinivasan, and Alexandre G. de Brevern</i>).</p> <p>9 Kernel Function Applications in Cheminformatics (<i>Aaron Smalter and Jun Huan</i>).</p> <p>10 <i>In Silico</i> Drug Design Using a Computational Intelligence Technique (<i>Soumi Sengupta and Sanghamitra Bandyopadhyay</i>).</p> <p><b>PART IV MICROARRAY DATA ANALYSIS.</b></p> <p>11 Integrated Differential Fuzzy Clustering for Analysis of Microarray Data (<i>Indrajit Saha and Ujjwal Maulik</i>).</p> <p>12 Identifying Potential Gene Markers Using SVM Classifier Ensemble (<i>Anirban Mukhopadhyay, Ujjwal Maulik, and Sanghamitra Bandyopadhyay</i>).</p> <p>13 Gene Microarray Data Analysis Using Parallel Point Symmetry-Based Clustering (<i>Ujjwal Maulik and Anasua Sarkar</i>).</p> <p><b>PART V SYSTEMS BIOLOGY.</b></p> <p>14 Techniques for Prioritization of Candidate Disease Genes (<i>Jieun Jeong and Jake Y. Chen</i>).</p> <p>15 Prediction of Protein–Protein Interactions (<i>Angshuman Bagchi</i>).</p> <p>16 Analyzing Topological Properties of Protein–Protein Interaction Networks: A Perspective Toward Systems Biology (<i>Malay Bhattacharyya and Sanghamitra Bandyopadhyay</i>).</p> <p>Index.</p>

"This collection of 16 papers, edited by Maulik (computer science and engineering, Jadavpur U., India), Bandyopadhyay (Indian Statistical Institute, India), and Wang (data and knowledge engineering, New Jersey Institute of Technology, US), brings together contributions from practitioners integrating computational intelligence and pattern analysis techniques for analyzing biological data, including sequence, structure, and microarray data. The material is organized into five sections that explore basic principles and methodologies of computational techniques, applications of computational intelligence and pattern analysis for biological sequence analysis, structural analysis; microarray data analysis, and systems biology." (<i>Reference and Research Book News</i>, February 2011)

<p><b>Dr. Ujjwal Maulik</b> is Professor of Computer Science and Engineering at Jadavpur University (India). He is the editor or author of five books and coauthor of more than 150 articles. Dr. Maulik is a Senior Member of IEEE and also a Humboldt Fellow.</p> <p><b>Dr. Sanghamitra Bandyopadhyay</b> is Professor at the Indian Statistical Institute. She is the editor or author of six books and coauthor of more than 180 articles. Dr. Bandyopadhyay is a Senior Member of IEEE and also a Humboldt Fellow.</p> <p><b>Dr. Jason T. L. Wang</b> is a Professor and Director of the Data and Knowledge Engineering Lab at the New Jersey Institute of Technology. He is the editor or author of six books and Executive Editor of the <i>World Scientific Book</i> Series on Science, Engineering, and Biology Informatics.</p>

<p><b>An expert review of recent developments in CI in biological informatics</b></p> <p>In the field of biological informatics, new methods of data collection that gather huge amounts of data and produce new data types have spurred advanced methods of searching for useful regularities or patterns in these data sets. Of these methods, computational intelligence has found particular favor among researchers. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques.</p> <p><i>Computational Intelligence and Pattern Analysis in Biological Informatics</i> brings together research articles by active practitioners, reporting recent advances in integrating computational intelligence and pattern analysis techniques for analyzing biological data in order to extract more meaningful information and insights from them. It covers highly relevant topics, including rational drug design and the involvement of microRNAs in human diseases. The book:</p> <ul> <li>Presents a description of some of CI's important components, fundamental concepts in pattern analysis, and different issues in biological informatics</li> <li>Gives detailed descriptions of the different applications of computational intelligence and pattern analysis techniques to biological informatics</li> <li>Provides details on analysis of sequences, structures, and microarray data, as well as an examination of topics in systems biology</li> </ul> <p>Packed with theoretical and experimental results, <i>Computational Intelligence and Pattern Analysis in Biological Informatics</i> deepens the understanding?of?the ways?in which the basic principles of computational intelligence and pattern analysis can be used for analyzing biological data in an efficient manner. Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, biochemistry, systems science, and information technology will find this unique volume a valuable tool.</p>

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