This supplement issue consists of 10 peer-reviewed papers and one review article based on the NIPS Workshop on New Problems and Methods in Computational Biology held at Whistler, Canada on December 18th, 2004. This workshop is designed to bring together machine learning and com putational biology researchers to develop fundamentally new methods for an alyzing biological data.
We received submissions both from the presenters at the worksho p as well as non-presenters. Submitted manuscripts were rigorously reviewed by at least two referees. The quality of each paper was evaluated on the contributions to biology as well as novelty as new machi ne learning methods. Since the NIPS conference is a leading machine learning conference, we require d technical novelty and mathematical rigor in methodology.
We would like to thank the workshop presenters and participants who made this special issue possible. Special thanks go to the  editors of BMC Bioinformatics who advised us in preparing the manuscripts. Finally we acknowledge the financial support by PASCAL (Pattern Analysis, Statistical Mode lling and
Computational Learning,) a newly launched European Network of Excellence (NoE).

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