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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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  • Fast track conference proceedings
  • Unique visibility
  • State of the art research

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)

Included in the following conference series:

Conference proceedings info: EvoBIO 2012.

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Table of contents (23 papers)

  1. Oral Contributions

  2. Poster Contributions

Other volumes

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

Keywords

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.

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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