Machine Learning for Bioinformatics
Editors: Yan-Qing Zhang and Jagath C. Rajapakse
John Wiley & Sons, 2008
Foreword
Preface
Chapter 1
Prof. S.Y. Kung (Princeton University, USA), Prof. Manwai Mak (The Hong Kong Polytechnic
University),
“Feature Selection for Genomic and Proteomic Data Mining”.
Chapter 2
Rajiv Menjoge and Prof. Roy Welsch (MIT),
“Comparing Variable Selection Methods in Gene Selection and Classification of Microarray
Data”.
Chapter 3
Dr. Hyunsoo Kim and Prof. Haesun Park, (Georgia Institute of Technology, USA),
“Adaptive Kernel Classifiers using Updating Matrix Decomposition for Biological Data
Analysis”.
Chapter 4
Shaoning Pang, Ilkka Havukkala, Yingjie Hu, and Prof. Nik Kasabov (Auckland University of
Technology, New Zealand),
“Bootstrapping Consistency Method for Optimal Gene Selection from Microarray Gene
Expression Data for Classification Problems”.
Chapter 5
Zhenyu Wang, Prof. Vasile Palade (Oxford University, UK)
“Fuzzy Gene Mining: A Fuzzy-based Framework for Cancer Microarray Data Analysis”.
Chapter 6
Dr. Guo-Zheng Li (Shanghai University, China) and Dr. Jack Y. Yang (Harvard University,
USA),
“Feature Selection for Ensemble Learning and Its Application”.
Chapter 7
Shandar Ahmad, Y. Hemajit Singh (Jamia Millia Islamia University, India), Marcos J. AraúzoBravo, Akinori Sarai (Kyushu Institute of Technology, Japan),
“Sequence-based prediction of residue-level properties in proteins”.
Chapter 8
Dongbo Bu (Univ. of Walerloo, Canada and Institute of Computing Technology, China), Shuai
Cheng Li (Univ. of Walerloo, Canada), Xin Gao (Univ. of Walerloo, Canada), Libo Yu (Univ. of
Walerloo, Canada), Jinbo Xu (Toyota Technological Institute at Chicago, USA), Prof. Ming Li
(Univ. of Walerloo, Canada),
“Consensus Approaches to Protein Structure Prediction”.
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Chapter 9
Prof. M. Palaniswami, Jayavardhana Rama (University of Melbourne, Australia)
“Kernel Methods for Protein Structure prediction”.
Chapter 10
Dr. Bo Jin and Prof. Yan-Qing Zhang, (Georgia State University, USA),
“Evolutionary Granular Kernel Trees Machines for Protein Subcellular Location Prediction”.
Chapter 11
Prof. Li Liao (University of Delaware, USA),
“Probabilistic models for long range features in biosequences”.
Chapter 12
Dr. Chandan K Reddy, Yao-Chung Weng and Hsiao-Dong Chiang (Cornel University),
“Neighborhood Profile Search for Motif Refinement”
Chapter 13
Prof. Jagath C. Rajapakse, L. S. HO (Nanyang Technological University, Singapore),
“Markov/Neural Model for Eukaryotic Promoter Recognition”.
Chapter 14
Xudong Xie, Shuanhu Wu and Prof. Hong Yan, (City University of Hong Kong, Hong Kong),
“Eukaryotic Promoter Detection Based on Word and Sequence Feature Selection and
Combination”.
Chapter 15
Dr. Mary Qu-Xuanyuan Yang (NIH, USA), Dr. David C. King (Pennsylvania State University,
USA) and Dr. Laura L. Elnitski (NIH, USA),
“Feature Characterization and Testing of Bidirectional Promoters in the Human Genome Significance and Applications in Human Genome Research”.
Chapter 16
Prof. Byoung-Tak Zhang and Jin-Wu Nam (Seoul National University, Korea),
“Supervised Learning Methods for microRNA Studies”.
Chapter 17
Phil Hyoun Lee and Prof. Hagit Shatkay (Queen's University, Canada),
“Machine Learning for Computational Haplotype Analysis”.
Chapter 18
Pritam Chanda, Prof. Aidong Zhang, Murali Ramanathan (University at Buffalo, The State
University of New York, USA),
“Machine Learning Applications in SNP-Disease Association Study”.
Chapter 19
Prof. Stephen Winters-Hilt (University of New Orleans, USA),
“Nanopore Cheminformatics based Studies of Individual Molecular Interactions”.
Chapter 20
Srivatsava Ranjit Ganta, Dr. John Gilbertson, Dr. Jyotsna Kasturi and Prof Raj Acharya,
(Penn State University, USA),
“An Information Fusion based framework for biomedical data mining”
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