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Titlebook: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics; 8th European Confere Clara Pizzuti,Marylyn D. Ritchie,Mario G

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發(fā)表于 2025-3-21 18:19:35 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
副標題8th European Confere
編輯Clara Pizzuti,Marylyn D. Ritchie,Mario Giacobini
視頻videohttp://file.papertrans.cn/318/317901/317901.mp4
概述Fast track conference proceeding.Unique visibility.State of the art research
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics; 8th European Confere Clara Pizzuti,Marylyn D. Ritchie,Mario G
出版日期Conference proceedings 2010
關鍵詞bioinformatics; data mining; evolution; evolutionary computation; genetics; learning; machine learning; mod
版次1
doihttps://doi.org/10.1007/978-3-642-12211-8
isbn_softcover978-3-642-12210-1
isbn_ebook978-3-642-12211-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE
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Role of Centrality in Network-Based Prioritization of Disease Genesthat the products of genes associated with similar diseases are likely to interact with each other heavily in a network of protein-protein interactions (PPIs). An important challenge for these applications, however, is the incomplete and noisy nature of PPI data. Random walk and network propagation
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Parallel Multi-Objective Approaches for Inferring Phylogeniess. Several single optimality criterion have been proposed for the phylogenetic reconstruction problem. However, different criteria may lead to conflicting phylogenies. In this scenario, a multi-objective approach can be useful since it could produce a set of optimal trees according to multiple crite
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An Evolutionary Model Based on Hill-Climbing Search Operators for Protein Structure Predictionputational biology. A new evolutionary model based on hill-climbing genetic operators is proposed to address the hydrophobic - polar model of the protein folding problem. The introduced model ensures an efficient exploration of the search space by implementing a problem-specific crossover operator a
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Finding Gapped Motifs by a Novel Evolutionary Algorithming the complex gene regulatory networks and understanding gene functions. In this work, we develop a novel motif finding algorithm based on a population-based stochastic optimization technique called Particle Swarm Optimization (PSO), which has been shown to be effective in optimizing difficult mul
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A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationshipst to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variations and the task of modeling interactions between them. We and others have previously developed algorithms to
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Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Cogredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many “gene expression signatures” have been developed, i.e. sets of genes whose expression values in
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