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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

  • Conference proceedings
  • © 2009

Overview

Editors:
  1. Clara Pizzuti

    1. Italian National Research Council (CNR), Institute for High-Performance Computing and Networking (ICAR), Rende (CS), Italy

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  2. Marylyn D. Ritchie

    1. Center for Human Genetics Research Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, USA

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  3. Mario Giacobini

    1. Department of Animal Production Epidemiology and Ecology, University of Torino, Grugliasco, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5483)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: EvoBIO 2009.

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Table of contents (17 papers)

  1. Front Matter

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  2. Association Study between Gene Expression and Multiple Relevant Phenotypes with Cluster Analysis

    • Zhenyu Jia, Yipeng Wang, Kai Ye, Qilan Li, Sha Tang, Shizhong Xu et al.
    Pages 1-12

  3. Gaussian Graphical Models to Infer Putative Genes Involved in Nitrogen Catabolite Repression in S. cerevisiae

    • Kevin Kontos, Bruno André, Jacques van Helden, Gianluca Bontempi
    Pages 13-24

  4. Chronic Rat Toxicity Prediction of Chemical Compounds Using Kernel Machines

    • Georg Hinselmann, Andreas Jahn, Nikolas Fechner, Andreas Zell
    Pages 25-36

  5. Simulating Evolution of Drosophila Melanogaster Ebony Mutants Using a Genetic Algorithm

    • Glennie Helles
    Pages 37-43

  6. Microarray Biclustering: A Novel Memetic Approach Based on the PISA Platform

    • Cristian Andrés Gallo, Jessica Andrea Carballido, Ignacio Ponzoni
    Pages 44-55

  7. F-score with Pareto Front Analysis for Multiclass Gene Selection

    • Piyushkumar A. Mundra, Jagath C. Rajapakse
    Pages 56-67

  8. A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms

    • Fernando E. B. Otero, Alex A. Freitas, Colin G. Johnson
    Pages 68-79

  9. Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks

    • Stephen D. Turner, Marylyn D. Ritchie, William S. Bush
    Pages 80-91

  10. Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease

    • Casey S. Greene, Jason M. Gilmore, Jeff Kiralis, Peter C. Andrews, Jason H. Moore
    Pages 92-103

  11. On the Efficiency of Local Search Methods for the Molecular Docking Problem

    • Jorge Tavares, Salma Mesmoudi, El-Ghazali Talbi
    Pages 104-115

  12. A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems

    • Daniela Besozzi, Paolo Cazzaniga, Giancarlo Mauri, Dario Pescini, Leonardo Vanneschi
    Pages 116-127

  13. Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets

    • Ajay Kumar Tanwani, Jamal Afridi, M. Zubair Shafiq, Muddassar Farooq
    Pages 128-139

  14. Evolutionary Approaches for Strain Optimization Using Dynamic Models under a Metabolic Engineering Perspective

    • Pedro Evangelista, Isabel Rocha, Eugénio C. Ferreira, Miguel Rocha
    Pages 140-151

  15. Clustering Metagenome Short Reads Using Weighted Proteins

    • Gianluigi Folino, Fabio Gori, Mike S. M. Jetten, Elena Marchiori
    Pages 152-163

  16. A Memetic Algorithm for Phylogenetic Reconstruction with Maximum Parsimony

    • Jean-Michel Richer, Adrien Goëffon, Jin-Kao Hao
    Pages 164-175

  17. Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary Optimization Algorithm

    • Rui Dilão, Daniele Muraro, Miguel Nicolau, Marc Schoenauer
    Pages 176-190

  18. Refining Genetic Algorithm Based Fuzzy Clustering through Supervised Learning for Unsupervised Cancer Classification

    • Anirban Mukhopadhyay, Ujjwal Maulik, Sanghamitra Bandyopadhyay
    Pages 191-202

  19. Back Matter

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Other volumes

  1. Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Keywords

About this book

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.

Editors and Affiliations

  • Italian National Research Council (CNR), Institute for High-Performance Computing and Networking (ICAR), Rende (CS), Italy

    Clara Pizzuti

  • Center for Human Genetics Research Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, USA

    Marylyn D. Ritchie

  • Department of Animal Production Epidemiology and Ecology, University of Torino, Grugliasco, Italy

    Mario Giacobini

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