Pattern Recognition in Bioinformatics

Pattern Recognition in Bioinformatics: An Introduction. - Pattern Recognition in Bioinformatics: An Introduction. - 1: Signal and Motif Detection; Gene Selection. - Machine Learning Prediction of Amino Acid Patterns in Protein N-myristoylation. - A Profile HMM for Recognition of Hormone Response Elements. - Graphical Approach to Weak Motif Recognition in Noisy Data Sets. - Comparative Gene Prediction Based on Gene Structure Conservation. - Computational Identification of Short Initial Exons. - Pareto-Gamma Statistic Reveals Global Rescaling in Transcriptomes of Low and High Aggressive Breast Cancer Phenotypes. - Investigating the Class-Specific Relevance of Predictor Sets Obtained from DDP-Based Feature Selection Technique. - A New Maximum-Relevance Criterion for Significant Gene Selection. - 2: Models of DNA, RNA, and Protein Structures. - Spectral Graph Partitioning Analysis of In Vitro Synthesized RNA Structural Folding. - Predicting Secondary Structure of All-Helical Proteins Using Hidden Markov Support Vector Machines. - Prediction of Protein Subcellular Localizations Using Moment Descriptors and Support Vector Machine. - Using Permutation Patterns for Content-Based Phylogeny. - 3: Biological Databases and Imaging. - The Immune Epitope Database and Analysis Resource. - Intelligent Extraction Versus Advanced Query: Recognize Transcription Factors from Databases. - Incremental Maintenance of Biological Databases Using Association Rule Mining. - Blind Separation of Multichannel Biomedical Image Patterns by Non-negative Least-Correlated Component Analysis. - Image and Fractal Information Processing for Large-Scale Chemoinformatics, Genomics Analyses and Pattern Discovery. - Hybridization of Independent Component Analysis, Rough Sets, and Multi-Objective Evolutionary Algorithms for Classificatory Decomposition of Cortical Evoked Potentials.