Personal tools
You are here: Home Previous Workshops MLCB2004

MLCB-2004 NIPS Computational Biology Workshop

NIPS 2004 Computational Biology Workshop

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, thus requires to combine 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 interactions, gene ontology and pathway databases, genetic variation data (such as SNPs), and an enormous amount of textual data in the biological and medical literature. The new types of scientific and clinical problems, require to develop new supervised and unsupervised learning approaches that can use these growing resources.

The goal of this workshop is to present emerging problems and machine learning techniques in computational biology. Speakers from the biology/bioinformatics community will present current research problems in bioinformatics, and we invite contributed talks on novel learning approaches 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 checkout the Call for contributions and the program.
Information about publication in a BMC bioinformatics special issue will be provided here.


  • Gal Chechik, Department of Computer Science, Stanford University
  • Christina Leslie, Center for Computational Learning Systems, Columbia University
  • Gunnar Rätsch, Friedrich Miescher Laboratory of the Max Planck Society
  • 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, The Technion
  • Michael I. Jordan, UC Berkeley
  • Alexander Hartemink, Duke University
  • Klaus-Robert Müller, Fraunhofer FIRST
  • William Stafford Noble, University of Washington
  • Bernhard Schölkopf, 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


If you are interested in contributing or have comments please send an e-mail to one of the organizers and check out the Call for contributions


The workshop is suported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning), a newly launched European Network of Excellence (NoE).

Page last updated on September 2, 2004

Document Actions