Evolutionary computation, machine learning and data mining in bioinformatics - Info and Reading Options

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Title Page -- Preface -- Organization -- Table of Contents -- Variable Genetic Operator Search for the Molecular Docking Problem -- Introduction -- Variable Genetic Operator Search -- Neighborhood Structures -- Encoding and Evaluation -- Genetic Operators -- Algorithm -- Experimentation and Analysis -- Settings -- Experiments -- Experiments with Local Search -- Conclusions and Future Work -- References -- Role of Centrality in Network-Based Prioritization of Disease Genes -- Introduction -- Background and Motivation -- Methods -- Reference Models for Statistical Adjustment -- Uniform Prioritization -- Results -- Datasets -- Experimental Setting -- Performance of Statistical Adjustment Schemes -- Performance of Uniform Prioritization -- Case Example -- Conclusion -- References -- Parallel Multi-Objective Approaches for Inferring Phylogenies -- Introduction -- Phylogenetic Reconstruction -- Maximum Parsimony -- Maximum Likelihood -- Multi-Objective Approaches for Phylogenetic Inference -- Parallel Strategies for PhyloMOEA -- Results -- Multi-Threaded Likelihood Function Scalability -- Parallel PhyloMOEA Scalability -- Final Remarks -- References -- An Evolutionary Model Based on Hill-Climbing Search Operators for Protein Structure Prediction -- Introduction -- The Bidimensional HP Protein Folding Problem -- Related Work -- An Evolutionary Model with Hill-Climbing Operators -- Hill-Climbing Mutation -- Hill-Climbing Crossover -- Diversification -- Numerical Experiments -- Conclusions and Future Work -- References -- Finding Gapped Motifs by a Novel Evolutionary Algorithm -- Introduction -- Algorithm -- Introduction to Particle Swarm Optimization -- Method Overview -- Solution Space and Fitness Function -- Initial Solutions and Number of Agents -- Modified PSO+ Update Rule for Discrete Problems -- Check Shift -- Gapped Motifs -- Post-processing

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