Machine Learning in Bioinformatics.
Title:
Machine Learning in Bioinformatics.
Author:
Zhang, Yanqing.
ISBN:
9780470397411
Personal Author:
Edition:
1st ed.
Physical Description:
1 online resource (476 pages)
Series:
Wiley Series in Bioinformatics Ser. ; v.4
Wiley Series in Bioinformatics Ser.
Contents:
MACHINE LEARNING IN BIOINFORMATICS -- CONTENTS -- Foreword -- Preface -- Contributors -- 1 Feature Selection for Genomic and Proteomic Data Mining -- 2 Comparing and Visualizing Gene Selection and Classification Methods for Microarray Data -- 3 Adaptive Kernel Classifiers Via Matrix Decomposition Updating for Biological Data Analysis -- 4 Bootstrapping Consistency Method for Optimal Gene Selection from Microarray Gene Expression Data for Classification Problems -- 5 Fuzzy Gene Mining: A Fuzzy-Based Framework for Cancer Microarray Data Analysis -- 6 Feature Selection for Ensemble Learning and Its Application -- 7 Sequence-Based Prediction of Residue-Level Properties in Proteins -- 8 Consensus Approaches to Protein Structure Prediction -- 9 Kernel Methods in Protein Structure Prediction -- 10 Evolutionary Granular Kernel Trees for Protein Subcellular Location Prediction -- 11 Probabilistic Models for Long-Range Features in Biosequences -- 12 Neighborhood Profile Search for Motif Refinement -- 13 Markov/Neural Model for Eukaryotic Promoter Recognition -- 14 Eukaryotic Promoter Detection Based on Word and Sequence Feature Selection and Combination -- 15 Feature Characterization and Testing of Bidirectional Promoters in the Human Genome-Significance and Applications in Human Genome Research -- 16 Supervised Learning Methods for MicroRNA Studies -- 17 Machine Learning for Computational Haplotype Analysis -- 18 Machine Learning Applications in SNP-Disease Association Study -- 19 Nanopore Cheminformatics-Based Studies of Individual Molecular Interactions -- 20 An Information Fusion Framework for Biomedical Informatics -- Index.
Abstract:
Yan-Qing Zhang, PhD, is an Associate Professor of Computer Science at the Georgia State University, Atlanta. His research interests include hybrid intelligent systems, neural networks, fuzzy logic, evolutionary computation, Yin-Yang computation, granular computing, kernel machines, bioinformatics, medical informatics, computational Web Intelligence, data mining, and knowledge discovery. He has coauthored two books, and edited one book and two IEEE proceedings. He is program co-chair of the IEEE 7th International Conference on Bioinformatics & Bioengineering (IEEE BIBE 2007) and 2006 IEEE International Conference on Granular Computing (IEEE-GrC2006). Jagath C. Rajapakse, PhD, is Professor of Computer Engineering and Director of the BioInformatics Research Centre, Nanyang Technological University. He is also Visiting Professor in the Department of Biological Engineering, Massachusetts Institute of Technology. He completed his MS and PhD degrees in electrical and computer engineering at University at Buffalo, State University of New York. Professor Rajapakse has published over 210 peer-reviewed research articles in the areas of neuroinformatics and bioinformatics. He serves as Associate Editor for IEEE Transactions on Medical Imaging and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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