This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
Author(s): Pradipta Maji, Sushmita Paul (auth.)
Edition: 1
Publisher: Springer International Publishing
Year: 2014
Language: English
Pages: 304
Tags: Computational Biology/Bioinformatics; Pattern Recognition; Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Imaging / Radiology
Front Matter....Pages i-xxii
Introduction to Pattern Recognition and Bioinformatics....Pages 1-42
Front Matter....Pages 43-43
Neural Network Tree for Identification of Splice Junction and Protein Coding Region in DNA....Pages 45-66
Design of String Kernel to Predict Protein Functional Sites Using Kernel-Based Classifiers....Pages 67-101
Front Matter....Pages 103-103
Rough Sets for Selection of Molecular Descriptors to Predict Biological Activity of Molecules....Pages 105-129
f -Information Measures for Selection of Discriminative Genes from Microarray Data....Pages 131-153
Identification of Disease Genes Using Gene Expression and Protein–Protein Interaction Data....Pages 155-170
Rough Sets for Insilico Identification of Differentially Expressed miRNAs....Pages 171-193
Front Matter....Pages 195-195
Grouping Functionally Similar Genes From Microarray Data Using Rough–Fuzzy Clustering....Pages 197-224
Mutual Information Based Supervised Attribute Clustering for Microarray Sample Classification....Pages 225-252
Possibilistic Biclustering for Discovering Value-Coherent Overlapping $$\delta $$ δ -Biclusters....Pages 253-276
Fuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images....Pages 277-297
Back Matter....Pages 299-304
