[apologies for multiple postings] ************************** Call for Papers ********************************* MLSB 09 Third International Workshop on Machine Learning in Systems Biology 5-6 September 2009, Ljubljana, Slovenia ****************************************************************************** http://mlsb09.ijs.si/ MOTIVATION Molecular biology and all the biomedical sciences are undergoing a true revolution as a result of the emergence and growing impact of a series of new disciplines/tools sharing the "-omics" suffix in their name. These include in particular genomics, transcriptomics, proteomics and metabolomics, devoted respectively to the examination of the entire systems of genes, transcripts, proteins and metabolites present in a given cell or tissue type. The availability of these new, highly effective tools for biological exploration is dramatically changing the way one performs research in at least two respects. First, the amount of available experimental data is not a limiting factor any more; on the contrary, there is a plethora of it. Given the research question, the challenge has shifted towards identifying the relevant pieces of information and making sense out of it (a "data mining" issue). Second, rather than focus on components in isolation, we can now try to understand how biological systems behave as a result of the integration and interaction between the individual components that one can now monitor simultaneously (so called "systems biology"). Taking advantage of this wealth of "genomic" information has become a conditio sine qua non for whoever ambitions to remain competitive in molecular biology and in the biomedical sciences in general. Machine learning naturally appears as one of the main drivers of progress in this context, where most of the targets of interest deal with complex structured objects: sequences, 2D and 3D structures or interaction networks. At the same time bioinformatics and systems biology have already induced significant new developments of general interest in machine learning, for example in the context of learning with structured data, graph inference, semi-supervised learning, system identification, and novel combinations of optimization and learning algorithms. OBJECTIVE The aim of this workshop is to contribute to the cross-fertilization between the research in machine learning methods and their applications to systems biology (i.e., complex biological and medical questions) by bringing together method developers and experimentalists. We encourage submissions bringing forward methods for discovering complex structures (e.g. interaction networks, molecule structures) and methods supporting genome-wide data analysis. LOCATION AND CO-LOCATION The workshop will take place 5-6 September 2009 at the Jozef Stefan Institute, Ljubljana, Slovenia. It will immediately precede ECML PKDD 2009, taking place 7-11 September 2009 in Bled, Slovenia (Bled is 30 miles from Ljubljana, transport will be organized). SUBMISSIONS INSTRUCTIONS For an oral presentation, please submit an extended abstract of maximum eight pages. Formatting instructions are available on the website of the workshop. Extended abstracts should be submitted online by 1 June 2009 via the Easychair submission system at http://www.easychair.org/conferences/?conf=mlsb09. The accepted submissions will be collected in the proceedings of the workshop. KEY DATES 01 June: deadline for submission of extended abstracts for oral presentation 03 July: notification for oral presentations 03 August: deadline for submission of abstracts for poster presentations 10 August: notification for posters & camera ready versions due 5-6 September: workshop TOPICS A non-exhaustive list of topics suitable for this workshop is given below: Methods Machine learning algorithms Bayesian methods Data integration/fusion Feature/subspace selection Clustering Biclustering/association rules Kernel methods Probabilistic inference Structured output prediction Systems identification Graph inference, completion, smoothing Semi-supervised learning Applications Sequence annotation Gene expression and post-transcriptional regulation Inference of gene regulation networks Gene prediction and whole genome association studies Metabolic pathway modeling Signaling networks Systems biology approaches to biomarker identification Rational drug design methods Metabolic reconstruction Protein function and structure prediction Protein-protein interaction networks Synthetic biology CONFIRMED INVITED SPEAKERS Ross D. King, Aberystwyth University, UK William Stafford Noble, University of Washington, USA MLSB09 PROGRAM CHAIRS Sašo Džeroski, Jozef Stefan Institute, Ljubljana, Slovenia Pierre Geurts, Department of EE and CS & GIGA-Research, University of Liège, Belgium Juho Rousu, Department of Computer Science, University of Helsinki, Finland SCIENTIFIC PROGRAM COMMITTEE Florence d'Alché-Buc, University of Evry, France Saso Dzeroski, Jozef Stefan Institute, Slovenia Paolo Frasconi, Università degli Studi di Firenze, Italy Cesare Furlanello, Fondazione Bruno Kessler, Trento, Italy Pierre Geurts, University of Liège, Belgium Mark Girolami, University of Glasgow, UK Dirk Husmeier, Biomathematics & Statistics Scotland, UK Samuel Kaski, Helsinki University of Technology, Finland Ross D. King, Aberystwyth University, UK Neil Lawrence, University of Manchester, UK Elena Marchiori, Vrije Universiteit Amsterdam, The Netherlands Yves Moreau, Katholieke Universiteit Leuven, Belgium William Stafford Noble, University of Washington, USA Gunnar Rätsch, FML, Max Planck Society, Tübingen Juho Rousu, University of Helsinki, Finland Céline Rouveirol, University of Paris XIII, France Yvan Saeys, University of Gent, Belgium Guido Sanguinetti, University of Sheffield, UK Ljupco Todorovski, University of Ljubljana, Slovenia Koji Tsuda, Max Planck Institute, Tuebingen Jean-Philippe Vert, Ecole des Mines, France Louis Wehenkel, University of Liège, Belgium Jean-Daniel Zucker, University of Paris XIII, France Blaz Zupan, University of Ljubljana, Slovenia LOCAL ORGANIZATION Ivica Slavkov, Dragi Kocev, Tina Anžič, Jozef Stefan Institute, Ljubljana, Slovenia