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Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics : 7th European Conference, EvoBIO 2009 T¼bingen, Germany, April 15-17, 2009 Proceedings - Clara Pizzuti

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

7th European Conference, EvoBIO 2009 T¼bingen, Germany, April 15-17, 2009 Proceedings

By: Clara Pizzuti (Editor), Marylyn D. Ritchie (Editor), Mario Giacobini (Editor)

Paperback | 2 April 2009

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Association Study between Gene Expression and Multiple Relevant Phenotypes with Cluster Analysis.- Gaussian Graphical Models to Infer Putative Genes Involved in Nitrogen Catabolite Repression in S. cerevisiae.- Chronic Rat Toxicity Prediction of Chemical Compounds Using Kernel Machines.- Simulating Evolution of Drosophila Melanogaster Ebony Mutants Using a Genetic Algorithm.- Microarray Biclustering: A Novel Memetic Approach Based on the PISA Platform.- F-score with Pareto Front Analysis for Multiclass Gene Selection.- A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms.- Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks.- Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease.- On the Efficiency of Local Search Methods for the Molecular Docking Problem.- A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems.- Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets.- Evolutionary Approaches for Strain Optimization Using Dynamic Models under a Metabolic Engineering Perspective.- Clustering Metagenome Short Reads Using Weighted Proteins.- A Memetic Algorithm for Phylogenetic Reconstruction with Maximum Parsimony.- Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary Optimization Algorithm.- Refining Genetic Algorithm Based Fuzzy Clustering through Supervised Learning for Unsupervised Cancer Classification.

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