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.