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Evolutionary computation, machine learning and data mining in bioinformatics : 11th European Conference : proceedings

作者: Leonardo Vanneschi; et al
出版商: Heidelberg : Springer, 2013.
叢書: Lecture notes in computer science, 7833
版本/格式:   圖書 : 英語
資料庫:WorldCat
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類型/形式: Kongress
文件類型: 圖書
所有的作者/貢獻者: Leonardo Vanneschi; et al
ISBN: 9783642371882 3642371884 9783642371899 3642371892
OCLC系統控制編碼: 844899199
描述: 215 S : Ill.
内容: Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseases.- Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experiments.- Inferring Human Phenotype Networks from Genome-Wide Genetic.- Knowledge-Constrained K-Medoids Clustering of Regulatory Rare Alleles for Burden Tests.- Feature Selection and Classification of High Dimensional Mass Spectrometry Data: A Genetic Programming Approach.- Structured Populations and the Maintenance of Sex.- Hybrid Multiobjective Artificial Bee Colony with Differential Evolution Applied to Motif Finding.- ACO-Based Bayesian Network Ensembles for the Hierarchical Classification of Ageing-Related Proteins.- Dimensionality Reduction via Isomap with Lock-Step and Elastic Measures for Time Series Gene Expression Classification.- Supervising Random Forest Using Attribute Interaction Networks.- Hybrid Genetic Algorithms for Stress Recognition in Optimal Use of Biological Expert Knowledge from Literature.- Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease.- A Multiobjective Proposal Based on the Firefly Algorithm for Inferring Phylogenies.- Mining for Variability in the Coagulation Pathway: A Systems Biology Approach.- Improving the Performance of CGPANN for Breast Cancer Diagnosis Using Crossover and Radial Basis Functions.- An Evolutionary Approach to Wetlands Design.- Impact of Different Recombination Methods in a Mutation-Specific MOEA for a Biochemical Application.- Cell-Based Metrics Improve the Detection of Gene-Gene Interactions Using Multifactor Dimensionality Reduction.- Emergence of Motifs in Model Gene Regulatory Networks.
叢書名: Lecture notes in computer science, 7833
責任: EvoBIO 2012, Vienna, Austria, April 3-5, 2013 ; Leonardo Vanneschi ... [et al.] (eds.).
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