Description:
Keynote Talk -- Exploiting Indirect Neighbours and Topological Weight to Predict Protein Function from Protein-Protein Interactions -- Database and Search -- A Database Search Algorithm for Identification of Peptides with Multiple Charges Using Tandem Mass Spectrometry -- Filtering Bio-sequence Based on Sequence Descriptor -- Automatic Extraction of Genomic Glossary Triggered by Query -- Frequent Subsequence-Based Protein Localization -- Bio Data Clustering -- gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data -- Automatic Orthologous-Protein-Clustering from Multiple Complete-Genomes by the Best Reciprocal BLAST Hits -- A Novel Clustering Method for Analysis of Gene Microarray Expression Data -- Heterogeneous Clustering Ensemble Method for Combining Different Cluster Results -- In-silico Diagnosis -- Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra -- Machine Learning Techniques and Chi-Square Feature Selection for Cancer Classification Using SAGE Gene Expression Profiles -- Generation of Comprehensible Hypotheses from Gene Expression Data -- Classification of Brain Glioma by Using SVMs Bagging with Feature Selection -- Missing Value Imputation Framework for Microarray Significant Gene Selection and Class Prediction -- Informative MicroRNA Expression Patterns for Cancer Classification.