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Call for Contributions MLCB-2008

Submission deadline October 12, 2008, 11:59pm (Samoa time).
Upload submissions directly to the MLCB2008 submission web site .

Workshop Description

The field of computational biology has seen dramatic growth over the past few years, in terms of newly available data, new scientific questions and new challenges 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 sources 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. These new types of scientific and clinical problems require novel supervised and unsupervised learning approaches that can use these growing resources.
The workshop will host presentations 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.

This year the workshop will follow a mini-symposium on Computational Biology that will take place in Vancouver on the afternoon of Thursday Dec 11th.

Submission instructions:

Researchers interested in contributing should upload an extended abstract of 1-6 pages in PDF format to the submission website HERE , by October 12, 2008, 11:59pm (Samoa time). No special style is required. Authors may use the NIPS style file, but are also free to use other styles as long as they use standard font size (11-12 pt) and standard margins (no smaller than the NIPS style margins).

All submissions will be anonymously peer reviewed and will be evaluated on the basis of their technical content. A strong submission to the workshop typically presents a new learning method that yields new biological insights, or applies an existing learning method to a new biological problem. However, submissions that improve upon existing methods for solving previously studied problems will also be considered. Examples of research presented in previous years can be found online .

Please note that accepted abstracts will be posted at Authors may submit two versions of their abstract, a longer version for review and a shorter version for posting to the web page. In addition, presentations will be video taped and published online as part of the website supported by Pascal.

The workshop allows submissions of papers that are under review or have been recently published in a conference or a journal. This is done to encourage presentation of mature research projects that are interesting to the community. The authors should clearly state any overlapping published work at time of submission. Authors of accepted abstracts will be invited to submit full length versions of their contributions for publication in a special issue of BMC Bioinformatics.


Program Committee

  • Pierre Baldi, UC Irvine
  • Kristin Bennett, Rensselaer Polytechnic Institute
  • Mathieu Blanchette, McGill University
  • Florence d'Alche, Universit√© d'Evry-Val d'Essonne, Genopole
  • Eleazar Eskin, UCLA
  • Brendan Frey, University of Toronto
  • Nir Friedman, The Hebrew University of Jerusalem
  • Michael I. Jordan, UC Berkeley
  • Alexander Hartemink, Duke University
  • Michal Linial, The Hebrew University of Jerusalem
  • Klaus-Robert Müller, Fraunhofer FIRST and Technical University Berlin
  • Dana Pe'er, Columbia University
  • Uwe Ohler, Duke University
  • Alexander Schliep, Max Planck Institute for Molecular Genetics
  • Bernhard Schölkopf, Max Planck Institute for Biological Cybernetics
  • Eran Segal, The Weizmann institute
  • Jean-Philippe Vert, Ecole des Mines de Paris
  • Eric Xing, Carnegie Melon University
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