Data Mining for Biomedical Applications

by Li, Jinyan; Yang, Qiang; Tan, Ah-hwee

• ISBN13: 9783540331049
• ISBN10: 3540331042
• Format: Paperback
• Copyright: 2006-04-15
• Publisher: Springer-Verlag New York Inc

Summary

This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with 1 keynote talks were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on protein-protein interactions, database and search, bio data clustering, and in-silico diagnosis.

Table of Contents

Keynote Talk
Exploiting Indirect Neighbours and Topological Weight to Predict Protein Function from Protein-Protein Interactions
Hon Nian Chua, Wing-Kin Sung, Limsoon Wong	1	(1)
Database and Search
A Database Search Algorithm for Identification of Peptides with Multiple Charges Using Tandem Mass Spectrometry
Kong Ning, Ket Fah Chong, Hon Wai Leong	2	(12)
Filtering Bio-sequence Based on Sequence Descriptor
Te-Wen Hsieh, Huang-Cheng Kuo, Jen-Peng Huang	14	(10)
Automatic Extraction of Genomic Glossary Triggered by Query
Jiao Li, Xiaoyan Zhu	24	(11)
Frequent Subsequence-Based Protein Localization
Osmar R. Zaiane, Yang Wang, Randy Goebel, Gregory Taylor	35	(13)
Bio Data Clustering
gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data
Haoliang Jiang, Shuigeng Zhou, Jihong Guan, Ying Zheng	48	(12)
Automatic Orthologous-Protein-Clustering from Multiple Complete-Genomes by the Best Reciprocal BLAST Hits
Sunshin Kim, Kwang Su Jung, Keun Ho Ryu	60	(11)
A Novel Clustering Method for Analysis of Gene Microarray Expression Data
Fei Luo, Juan Liu	71	(11)
Heterogeneous Clustering Ensemble Method for Combining Different Cluster Results
Hye-Sung Yoon, Sun-Young Ahn, Sang-Ho Lee, Sung-Bum Cho, Ju Han Kim	82	(11)
In-silico Diagnosis
Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra
Vanathi Gopalakrishnan, Philip Ganchev, Srikanth Ranganathan, Robert Bowser	93	(13)
Machine Learning Techniques and Chi-Square Feature Selection for Cancer Classification Using SAGE Gene Expression Profiles
Xin Jin, Anbang Xu, Rongfang Bie, Ping Guo	106	(10)
Generation of Comprehensible Hypotheses from Gene Expression Data
Yuan Jiang, Ming Li, Zhi-Hua Zhou	116	(8)
Classification of Brain Glioma by Using SVMs Bagging with Feature Selection
Guo-Zheng Li, Tian-Yu Liu, Victor S. Cheng	124	(7)
Missing Value Imputation Framework for Microarray Significant Gene Selection and Class Prediction
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence Dooley	131	(12)
Informative MicroRNA Expression Patterns for Cancer Classification
Yun Zheng, Chee Keong Kwoh	143	(12)
Author Index	155