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Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics : 7th European Conference, EvoBIO 2009 Tübingen, Germany, April 15-17, 2009 Proceedings / edited by Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

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Format:
Book
Contributor:
Pizzuti, Clara, editor.
Ritchie, Marylyn D., editor.
Giacobini, Mario, editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
LNCS sublibrary. Theoretical computer science and general issues ; SL 1, 5483.
Theoretical Computer Science and General Issues ; 5483
Language:
English
Subjects (All):
Computer programming.
Computers.
Algorithms.
Bioinformatics.
Pattern perception.
Artificial intelligence.
Programming Techniques.
Computation by Abstract Devices.
Algorithm Analysis and Problem Complexity.
Computational Biology/Bioinformatics.
Pattern Recognition.
Artificial Intelligence.
Local Subjects:
Programming Techniques.
Computation by Abstract Devices.
Algorithm Analysis and Problem Complexity.
Computational Biology/Bioinformatics.
Pattern Recognition.
Artificial Intelligence.
Physical Description:
1 online resource (XII, 203 pages).
Edition:
First edition 2009.
Contained In:
Springer eBooks
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
System Details:
text file PDF
Summary:
This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tübingen, Germany, in April 2009 colocated with the Evo* 2009 events. The 17 revised full papers were carefully reviewed and selected from 44 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.
Contents:
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.
Other Format:
Printed edition:
ISBN:
978-3-642-01184-9
9783642011849
Access Restriction:
Restricted for use by site license.

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