Machine Learning in Bioinformatics / Wiley Series in Bioinformatics (PDF)

Foreword. Preface. Contributors. 1 Feature Selection for Genomic and Proteomic Data Mining (Sun-Yuan Kung and Man-Wai Mak). 2 Comparing and Visualizing Gene Selection and Classification Methods for Microarray Data (Rajiv S. Menjoge and Roy E. Welsch). 3 Adaptive Kernel Classifiers Via Matrix Decomposition Updating for Biological Data Analysis (Hyunsoo Kim and Haesun Park). 4 Bootstrapping Consistency Method for Optimal Gene Selection from Microarray Gene Expression Data for Classification Problems (Shaoning Pang, Ilkka Havukkala, Yingjie Hu, and Nikola Kasabov). 5 Fuzzy Gene Mining: A Fuzzy-Based Framework for Cancer Microarray Data Analysis (Zhenyu Wang and Vasile Palade). 6 Feature Selection for Ensemble Learning and Its Application (Guo-Zheng Li and Jack Y. Yang). 7 Sequence-Based Prediction of Residue-Level Properties in Proteins (Shandar Ahmad, Yemlembam Hemjit Singh, Marcos J. Araúzo-Bravo, and Akinori Sarai). 8 Consensus Approaches to Protein Structure Prediction (Dongbo Bu, ShuaiCheng Li, Xin Gao, Libo Yu, Jinbo Xu, and Ming Li). 9 Kernel Methods in Protein Structure Prediction (Jayavardhana Gubbi, Alistair Shilton, and Marimuthu Palaniswami). 10 Evolutionary Granular Kernel Trees for Protein Subcellular Location Prediction (Bo Jin and Yan-Qing Zhang). 11 Probabilistic Models for Long-Range Features in Biosequences (Li Liao). 12 Neighborhood Profile Search for Motif Refinement (Chandan K. Reddy, Yao-Chung Weng, and Hsiao-Dong Chiang). 13 Markov/Neural Model for Eukaryotic Promoter Recognition (Jagath C. Rajapakse and Sy Loi Ho). 14 Eukaryotic Promoter Detection Based on Word and Sequence Feature Selection and Combination (Xudong Xie, Shuanhu Wu, and Hong Yan). 15 Feature Characterization and Testing of Bidirectional Promoters in the Human Genome--Significance and Applications in Human Genome Research (Mary Q. Yang, David C. King, and Laura L. Elnitski). 16 Supervised Learning Methods for MicroRNA Studies (Byoung-Tak Zhang and Jin-Wu Nam). 17 Machine Learning

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.

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