Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

1. Front Matter

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2. Oral Contributions

   1. Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseases

      • Delaney Granizo-Mackenzie, Jason H. Moore

      Pages 1-10

   2. Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experiments

      • Jie Tan, Gavin D. Grant, Michael L. Whitfield, Casey S. Greene

      Pages 11-22

   3. Inferring Human Phenotype Networks from Genome-Wide Genetic Associations

      • Christian Darabos, Kinjal Desai, Richard Cowper-Sal·lari, Mario Giacobini, Britney E. Graham, Mathieu Lupien et al.

      Pages 23-34

   4. Knowledge-Constrained K-Medoids Clustering of Regulatory Rare Alleles for Burden Tests

      • R. Michael Sivley, Alexandra E. Fish, William S. Bush

      Pages 35-42

   5. Feature Selection and Classification of High Dimensional Mass Spectrometry Data: A Genetic Programming Approach

      • Soha Ahmed, Mengjie Zhang, Lifeng Peng

      Pages 43-55

   6. Structured Populations and the Maintenance of Sex

      • Peter A. Whigham, Grant Dick, Alden Wright, Hamish G. Spencer

      Pages 56-67

   7. Hybrid Multiobjective Artificial Bee Colony with Differential Evolution Applied to Motif Finding

      • David L. González-Álvarez, Miguel A. Vega-Rodríguez

      Pages 68-79

   8. ACO-Based Bayesian Network Ensembles for the Hierarchical Classification of Ageing-Related Proteins

      • Khalid M. Salama, Alex A. Freitas

      Pages 80-91

   9. Dimensionality Reduction via Isomap with Lock-Step and Elastic Measures for Time Series Gene Expression Classification

      • Carlotta Orsenigo, Carlo Vercellis

      Pages 92-103

   10. Supervising Random Forest Using Attribute Interaction Networks

       • Qinxin Pan, Ting Hu, James D. Malley, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore

       Pages 104-116

3. Poster Contributions

   1. Hybrid Genetic Algorithms for Stress Recognition in Reading

      • Nandita Sharma, Tom Gedeon

      Pages 117-128

   2. Optimal Use of Biological Expert Knowledge from Literature Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease

      • Arvis Sulovari, Jeff Kiralis, Jason H. Moore

      Pages 129-140

   3. A Multiobjective Proposal Based on the Firefly Algorithm for Inferring Phylogenies

      • Sergio Santander-Jiménez, Miguel A. Vega-Rodríguez

      Pages 141-152

   4. Mining for Variability in the Coagulation Pathway: A Systems Biology Approach

      • Davide Castaldi, Daniele Maccagnola, Daniela Mari, Francesco Archetti

      Pages 153-164

   5. Improving the Performance of CGPANN for Breast Cancer Diagnosis Using Crossover and Radial Basis Functions

      • Timmy Manning, Paul Walsh

      Pages 165-176

   6. An Evolutionary Approach to Wetlands Design

      • Marco Gaudesi, Andrea Marion, Tommaso Musner, Giovanni Squillero, Alberto Tonda

      Pages 177-187

   7. Impact of Different Recombination Methods in a Mutation-Specific MOEA for a Biochemical Application

      • Susanne Rosenthal, Nail El-Sourani, Markus Borschbach

      Pages 188-199

   8. Cell-Based Metrics Improve the Detection of Gene-Gene Interactions Using Multifactor Dimensionality Reduction

      • Jonathan M. Fisher, Peter Andrews, Jeff Kiralis, Nicholas A. Sinnott-Armstrong, Jason H. Moore

      Pages 200-211

   9. Emergence of Motifs in Model Gene Regulatory Networks

      • Marcin Zagórski

      Pages 212-215

This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.

• evolutionary algorithms
• genetic programming
• genome
• machine learning
• phenotype networks
• algorithm analysis and problem complexity

• ISEGI, Universidade Nova de Lisboa, Lisboa, Portugal

  Leonardo Vanneschi

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

  William S. Bush

• Department of Veterinary Sciences, University of Torino, Grugliasco, Italy

  Mario Giacobini

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