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Call for Contributions

Deadline for submission of extended abstracts was October 15, 2004 Deadline for submission is over. Decisions about accepted papers were sent out in November 2004

Workshop Description

The field of computational biology has seen a dramatic growth over the past few years, both in terms of new available data, new scientific questions and new challenges and for learning and inference. In particular, biological data is often relationally structured and highly diverse, and thus requires combining multiple weak evidence from heterogeneous sources. These could include sequenced genomes of a variety of organisms, gene expression data from multiple technologies, protein sequence and 3D structural data, protein interaction data, gene ontology and pathway databases, genetic variation data (such as SNPs), and an enormous amount of text data in the biological and medical literature. The new types of scientific and clinical problems require novel supervised and unsupervised learning approaches that can use these growing resources.
The workshop will host presentation of emerging problems and machine learning techniques in computational biology. We encourage contributions describing either progress on new bioinformatics problems or work on established problems using methods that are substantially different from standard approaches. Kernel methods, graphical models, feature selection and other techniques applied to relevant bioinformatics problems would all be appropriate for the workshop.

Please see the workshop's web page for further information.

Submission instructions:

Researchers interested in contributing should send an extended abstract of up to 4 pages (postscript or pdf format) to nips-compbio@tuebingen.mpg.de by October 15, 2004. The workshop organizers will invite submissions of full length versions of accepted workshop contributions for publication in a special issue of a BMC Bioinformatics.

Organizers

  • Gal Chechik, Department of Computer Science, Stanford University
  • Christina Leslie, Center for Computational Learning Systems, Columbia University
  • Gunnar Rätsch, Max Planck Institute for Biological Cybernetics (Tuebingen) and Fraunhofer FIRST (Berlin)
  • Koji Tsuda, Max Planck Institute for Biological Cybernetics (Tuebingen) and AIST Computational Biology Research Center (Tokyo)

Program Committee:

  • Pierre Baldi, UC Irvine
  • Kristin Bennett, Rensselaer Polytechnic Institute
  • Nello Cristianini, UC Davis
  • Eleazar Eskin, UC San Diego
  • Nir Friedman, Hebrew University and Harvard
  • Dan Geiger, Technion
  • Michael I. Jordan, UC Berkeley
  • Alexander Hartemink, Duke University
  • Klaus-Robert Mueller, Fraunhofer FIRST
  • William Stafford Noble, University of Washington
  • Bernhard Schoelkopf, Max Planck Institute for Biological Cybernetics
  • Alexander Schliep, Max Planck Institute for Molecular Genetics
  • Eran Segal, Stanford University
  • Jean-Philippe Vert, Ecole des Mines de Paris
The workshop is suported by the European PASCAL network, (Pattern Analysis, Statistical Modelling and Computational Learning).
Page last updated on September 2, 2004

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