Data Mining for Biomedical Applications

Chapter 1 Exploiting Indirect Neighbours and Topological Weight to Predict Protein Function from Protein-Protein Interactions

Chapter 2 A Database Search Algorithm for Identification of Peptides with Multiple Charges Using Tandem Mass Spectrometry

Chapter 3 Filtering Bio-sequence Based on Sequence Descriptor

Chapter 4 Automatic Extraction of Genomic Glossary Triggered by Query

Chapter 5 Frequent Subsequence-Based Protein Localization

Chapter 6 gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data

Chapter 7 Automatic Orthologous-Protein-Clustering from Multiple Complete-Genomes by the Best Reciprocal BLAST Hits

Chapter 8 A Novel Clustering Method for Analysis of Gene Microarray Expression Data

Chapter 9 Heterogeneous Clustering Ensemble Method for Combining Different Cluster Results

Chapter 10 Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra

Chapter 11 Machine Learning Techniques and Chi-Square Feature Selection for Cancer Classification Using SAGE Gene Expression Profiles

Chapter 12 Generation of Comprehensible Hypotheses from Gene Expression Data

Chapter 13 Classification of Brain Glioma by Using SVMs Bagging with Feature Selection

Chapter 14 Missing Value Imputation Framework for Microarray Significant Gene Selection and Class Prediction

Chapter 15 Informative MicroRNA Expression Patterns for Cancer Classification