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Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

10th European Conference, EvoBIO 2012, Málaga, Spain, April 11-13, 2012, Proceedings

  • Conference proceedings
  • © 2012

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Editors:
  1. Mario Giacobini

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

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  2. Leonardo Vanneschi

    1. Universidade Nove de Lisboa, ISEGI, 1070-312 Lisboa, Portugal and University of Milano-Bicocca, D.I.S.Co., Viale Sarca 336, 20126 Milan, Italy

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  3. William S. Bush

    1. Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, Nashville, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7246)

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

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Conference proceedings info: EvoBIO 2012.

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About this book

This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, held in Málaga, Spain, in April 2012 co-located with the Evo* 2012 events.
The 15 revised full papers presented together with 8 poster papers were carefully reviewed and selected from numerous submissions. Computational Biology is a wide and varied discipline, incorporating aspects of statistical analysis, data structure and algorithm design, machine learning, and mathematical modeling toward the processing and improved understanding of biological data. Experimentalists now routinely generate new information on such a massive scale that the techniques of computer science are needed to establish any meaningful result. As a consequence, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.

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Table of contents (23 papers)

  1. Front Matter

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  2. Oral Contributions

    1. Automatic Task Decomposition for the NeuroEvolution of Augmenting Topologies (NEAT) Algorithm

      • Timmy Manning, Paul Walsh
      Pages 1-12

    2. Evolutionary Reaction Systems

      • Luca Manzoni, Mauro Castelli, Leonardo Vanneschi
      Pages 13-25

    3. Optimizing the Edge Weights in Optimal Assignment Methods for Virtual Screening with Particle Swarm Optimization

      • Lars Rosenbaum, Andreas Jahn, Andreas Zell
      Pages 26-37

    4. Lévy-Flight Genetic Programming: Towards a New Mutation Paradigm

      • Christian Darabos, Mario Giacobini, Ting Hu, Jason H. Moore
      Pages 38-49

    5. Understanding Zooplankton Long Term Variability through Genetic Programming

      • Simone Marini, Alessandra Conversi
      Pages 50-61

    6. Inferring Disease-Related Metabolite Dependencies with a Bayesian Optimization Algorithm

      • Holger Franken, Alexander Seitz, Rainer Lehmann, Hans-Ulrich Häring, Norbert Stefan, Andreas Zell
      Pages 62-73

    7. A GPU-Based Multi-swarm PSO Method for Parameter Estimation in Stochastic Biological Systems Exploiting Discrete-Time Target Series

      • Marco S. Nobile, Daniela Besozzi, Paolo Cazzaniga, Giancarlo Mauri, Dario Pescini
      Pages 74-85

    8. Tracking the Evolution of Cooperation in Complex Networked Populations

      • Flávio L. Pinheiro, Francisco C. Santos, Jorge M. Pacheco
      Pages 86-96

    9. GeNet: A Graph-Based Genetic Programming Framework for the Reverse Engineering of Gene Regulatory Networks

      • Leonardo Vanneschi, Matteo Mondini, Martino Bertoni, Alberto Ronchi, Mattia Stefano
      Pages 97-109

    10. Comparing Multiobjective Artificial Bee Colony Adaptations for Discovering DNA Motifs

      • David L. González-Álvarez, Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido, Juan M. Sánchez-Pérez
      Pages 110-121

    11. The Role of Mutations in Whole Genome Duplication

      • Qinxin Pan, Christian Darabos, Jason H. Moore
      Pages 122-133

    12. Comparison of Methods for Meta-dimensional Data Analysis Using in Silico and Biological Data Sets

      • Emily R. Holzinger, Scott M. Dudek, Alex T. Frase, Brooke Fridley, Prabhakar Chalise, Marylyn D. Ritchie
      Pages 134-143

    13. Inferring Phylogenetic Trees Using a Multiobjective Artificial Bee Colony Algorithm

      • Sergio Santander-Jiménez, Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido, Juan M. Sánchez-Pérez
      Pages 144-155

    14. Prediction of Mitochondrial Matrix Protein Structures Based on Feature Selection and Fragment Assembly

      • Gualberto Asencio-Cortés, Jesús S. Aguilar-Ruiz, Alfonso E. Márquez-Chamorro, Roberto Ruiz, Cosme E. Santiesteban-Toca
      Pages 156-167

  3. Poster Contributions

    1. Feature Selection for Lung Cancer Detection Using SVM Based Recursive Feature Elimination Method

      • Kesav Kancherla, Srinivas Mukkamala
      Pages 168-176

    2. Measuring Gene Expression Noise in Early Drosophila Embryos: The Highly Dynamic Compartmentalized Micro-environment of the Blastoderm Is One of the Main Sources of Noise

      • Alexander V. Spirov, Nina E. Golyandina, David M. Holloway, Theodore Alexandrov, Ekaterina N. Spirova, Francisco J. P. Lopes
      Pages 177-188

    3. Artificial Immune Systems Perform Valuable Work When Detecting Epistasis in Human Genetic Datasets

      • Delaney Granizo-Mackenzie, Jason H. Moore
      Pages 189-200

    4. A Biologically Informed Method for Detecting Associations with Rare Variants

      • Carrie C. Buchanan, John R. Wallace, Alex T. Frase, Eric S. Torstenson, Sarah A. Pendergrass, Marylyn D. Ritchie
      Pages 201-210

    5. Complex Detection in Protein-Protein Interaction Networks: A Compact Overview for Researchers and Practitioners

      • Clara Pizzuti, Simona E. Rombo, Elena Marchiori
      Pages 211-223
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Other volumes

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

Editors and Affiliations

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

    Mario Giacobini

  • Universidade Nove de Lisboa, ISEGI, 1070-312 Lisboa, Portugal and University of Milano-Bicocca, D.I.S.Co., Viale Sarca 336, 20126 Milan, Italy

    Leonardo Vanneschi

  • Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, Nashville, USA

    William S. Bush

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