<html><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">[apologies for multiple postings]<br><br><br>********************** Second Call for Papers **************************<br><br> 2nd International Workshop on Machine Learning in Systems Biology<br> 13-14 September 2008, Brussels, Belgium<br><br>************************************************************************<br><br> <a href="http://www.montefiore.ulg.ac.be/services/stochastic/mlsb08">http://www.montefiore.ulg.ac.be/services/stochastic/mlsb08</a><br><br><br>MOTIVATION<br><br><br>Molecular biology and also all the biomedical sciences are undergoing<br>a true revolution as a result of the emergence and growing impact of a<br>series of new disciplines/tools sharing the "-omics" suffix in<br>theirname. These include in particular genomics, transcriptomics,<br>proteomics and metabolomics devoted respectively to the examination of<br>the entire systems of genes, transcripts, proteins and metabolites<br>present in a given cell or tissue type.<br><br>The availability of these new, highly effective tools for biological<br>exploration is dramatically changing the way one performs research in<br>at least two respects. First of all, the amount of available<br>experimental data is not at all a limiting factor any more; on the<br>contrary, there is a plethora of it. The challenge has shifted<br>towards identifying the relevant pieces of information given the<br>question, and how to make sense out of it (a "data mining"<br>issue). Secondly, rather than to focus on components in isolation, we<br>can now try to understand how biological systems behave as the result<br>of the integration and interaction between the individual components<br>that one can now monitor simultaneously (so called "systems biology").<br><br>Taking advantage of this wealth of "genomic" information has become<br>a conditio sine qua non for whoever ambitions to remain competitive in<br>molecular biology and more generally in biomedical sciences. Machine<br>learning naturally appears as one of the main drivers of progress in<br>this context, where most of the targets of interest deal with complex<br>structured objects: sequences, 2D and 3D structures or interaction<br>networks. At the same time bioinformatics and systems biology have<br>already induced significant new developments of general interest in<br>machine learning, for example in the context of learning with<br>structured data, graph inference, semi-supervised learning, system<br>identification, and novel combinations of optimization and learning<br>algorithms.<br><br><br>OBJECTIVE<br><br><br>The aim of this workshop is to contribute to the cross-fertilization<br>between the research in machine learning methods and their<br>applications to complex biological and medical questions by bringing<br>together method developers and experimentalists. We encourage<br>submissions bringing forward methods for discovering complex<br>structures (e.g. interaction networks, molecule structures) and<br>methods supporting genome-wide data analysis.<br><br>A non-exhaustive list of topics suitable for this workshop:<br><br>Methods<br><br>Machine Learning Algorithms<br>Bayesian Methods<br>Data integration/fusion<br>Feature/subspace selection<br>Clustering<br>Biclustering/association rules<br>Kernel Methods<br>Probabilistic Inference<br>Structured output prediction<br>Systems identification<br>Graph inference, completion, smoothing<br>Semi-supervised learning<br><br>Applications<br><br>Sequence Annotation<br>Gene Expression and post-transcriptional regulation<br>Inference of gene regulation networks<br>Gene Prediction and whole genome association studies<br>Metabolic pathway modeling<br>Signaling networks<br>Systems biology approaches to biomarker identification<br>Rational drug design methods<br>Metabolic Reconstruction<br>Protein Structure Prediction<br>Protein Function Prediction<br>Protein-protein interaction networks<br><br><br>SUBMISSIONS OF EXTENDED ABSTRACTS<br><br><br>We invite to submit an extended abstract of maximum 8 pages. Each<br>extended abstract must be submitted by June 15 2008 electronically via<br>the Easychair submission system:<br><a href="http://www.easychair.org/conferences/?conf=mlsb08">http://www.easychair.org/conferences/?conf=mlsb08</a><br><br>Formatting instructions can be found on the workshop website<br><a href="http://www.montefiore.ulg.ac.be/services/stochastic/mlsb08">http://www.montefiore.ulg.ac.be/services/stochastic/mlsb08</a><br><br>The extended abstracts will be reviewed by the scientific programme<br>committee. The papers will be selected for oral or poster presentation<br>according to their originality and relevance to the workshop<br>topics. Electronic versions of the extended abstracts will be<br>accessible to the participants prior to the conference and will be<br>made publicly available on the conference web site after the<br>conference. It is also planned to publish these papers in a special<br>volume of a bioinformatics journal.<br><br><br>SUBMISSION OF POSTER PRESENTATIONS<br><br><br>We invite you also to apply for poster presentations on topics of<br>relevance to the workshop. Each poster presentation should be<br>described in a 1 page summary and be submitted by August 20, 2008 via<br>the Easychair submission system:<br><a href="http://www.easychair.org/conferences/?conf=mlsb08">http://www.easychair.org/conferences/?conf=mlsb08</a><br><br>Poster summaries must follow the same formatting instructions as<br>the extended abstract, but should not exceed one page.<br><br><br>IMPORTANT DATES<br><br><br>- 15 June: deadline for submissions of extended abstracts<br>- 15 July: notification of acceptance to authors<br>- 25 August: camera-ready versions of extended abstracts<br><br>- 20 August: deadline for submissions of poster presentations<br>- 25 August: notification of acceptance to authors<br><br>- 13-14 September: workshop<br><br><br>LOCATION<br><br><br>The workshop will take place in Brussels at the Palais des Académies<br>of Académie royale des Sciences, des Lettres et des Beaux-Arts de<br>Belgique.<br><br><br>CONTACT<br><br><br>For further information, please contact <a href="mailto:mlsb08@gmail.com">mlsb08@gmail.com</a> or see<br>the conference website:<br><a href="http://www.montefiore.ulg.ac.be/services/stochastic/mlsb08">http://www.montefiore.ulg.ac.be/services/stochastic/mlsb08</a><br><br><br>MLSB08 CHAIRS<br><br><br>Louis Wehenkel and Pierre Geurts, GIGA-Research, University of Liège,<br>Belgium<br>Florence d’Alché-Buc, IBISC CNRS FRE 2873, University of<br>Evry-Val d’Essonne, France<br>Yves Moreau, ESAT, Katholieke Universiteit Leuven, Belgium<br><br><br>SCIENTIFIC PROGRAMME COMMITTEE<br><br><br>Florence d’Alché-Buc (University of Evry, France)<br>Christophe Ambroise (University of Evry, France)<br>Pierre Geurts (University of Liège, Belgium)<br>Mark Girolami (University of Glasgow, UK)<br>Samuel Kaski (University of Helsinki, Finland)<br>Kathleen Marchal (Katholieke Universiteit Leuven, Belgium)<br>Elena Marchiori (Vrije Universiteit Amsterdam, The Netherlands)<br>Yves Moreau (Katholieke Universiteit Leuven, Belgium)<br>Gunnar Rätsch (FML, Max Planck Society, Tübingen)<br>Juho Rousu (University of Helsinki, Finland)<br>Céline Rouveirol (University of Paris XIII, France)<br>Yvan Saeys (University of Gent, Belgium)<br>Rodolphe Sepulchre (University of Liège, Belgium)<br>Koji Tsuda (Max Planck Institute, Tuebingen)<br>Jacques Van Helden (Université Libre de Bruxelles, Belgium)<br>Kristel Van Steen (University of Liège, Belgium)<br>Jean-Philippe Vert (Ecole des Mines, France)<br>Louis Wehenkel (University of Liège, Belgium)<br>David Wild (University of Warwick, UK)<br>Jean-Daniel Zucker (University of Paris XIII, France)<br></body></html>