* Apologies for multiple postings * * Please feel free to forward to any other relevant mailing lists * ************************** Call for Papers ***************************** MLSB 2010 The Fourth International Workshop on Machine Learning in Systems Biology 15-16 October 2010, Edinburgh, Scotland *********************************************************************** http://mlsb10.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. The Workshop is organized as "core - event" of Pattern Analysis, Statistical Modelling and Computational Learning - Network of Excellence 2 (PASCAL 2, http://www.pascal-network.org/) 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 15-16 October 2010 at the Edinburgh International Conference Centre and the Informatics Forum of the University of Edinburgh. It will be part of the wokshop program of ICSB 2010, The 11th International Conference on Systems Biology (11-14 OCT 2010, http://www.icsb2010.org.uk/). SUBMISSIONS INSTRUCTIONS We invite you to submit an extended abstract of up to 4 pages describing new or recently published (2010) results, formatted according to the Springer Lecture Notes in Computer Science style. Each extended abstract must be submitted online via the Easychair submission system: http://www.easychair.org/conferences/?conf=mlsb10 The extended abstracts will be reviewed by the scientific programme committee. They will be selected for oral or poster presentation according to their originality and relevance to the workshop topics. Electronic versions of the extended abstracts will be accessible to the participants prior to the conference, distributed in hardcopy form to participants at the conference, and will be made publicly available on the conference web site after the conference. However, the book of abstracts will not be published and the extended abstracts will not constitute a formal publication. We expect that authors of selected contributions will be invited to submit full papers to special issues of high-ranking Machine Learning/Systems Biology journals. KEY DATES 15 May: Submission site open 25 June: deadline for submission of extended abstracts 25 July: notification of acceptance 15-16 October: 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 INVITED SPEAKERS (confirmed) Florence d'Alche Buc, Universite d'Evry-Val d'Essonne, Evry, France Nir Friedman, The Hebrew University of Jerusalem, Jerusalem, Israel Ursula Kummer, BIOQUANT, University of Heidelberg, Germany Hans Lehrach, Max Planck Institute for Molecular Genetics, Berlin, Germany Vebjorn Ljosa, The Broad Institute of MIT and Harvard, USA MLSB10 PROGRAM CHAIRS Saöo Dûeroski, Jozef Stefan Institute, Ljubljana, Slovenia Simon Rogers, University of Glasgow, UK Guido Sanguinetti, University of Sheffield/University of Edinburgh, UK SCIENTIFIC PROGRAM COMMITTEE (tentative) Florence d'AlchÈ-Buc, University of Evry, France Paolo Frasconi, Universit‡ degli Studi di Firenze, Italy Cesare Furlanello, Fondazione Bruno Kessler, Trento, Italy Pierre Geurts, University of LiËge, 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 R‰tsch, FML, Max Planck Society, T¸bingen Juho Rousu, University of Helsinki, Finland CÈline Rouveirol, University of Paris XIII, France Yvan Saeys, University of Gent, Belgium Ljupco Todorovski, University of Ljubljana, Slovenia Koji Tsuda, Max Planck Institute, Tuebingen Jean-Philippe Vert, Ecole des Mines, France Louis Wehenkel, University of LiËge, Belgium Jean-Daniel Zucker, University of Paris XIII, France Blaz Zupan, University of Ljubljana, Slovenia LOCAL ORGANIZATION Fiona Clark, University of Edinburgh, UK Dragi Kocev, Jozef Stefan Institute, Ljubljana, Slovenia (webmaster) -- Dr. Simon Rogers Lecturer in Inference Department of Computing Science University of Glasgow G12 8QQ, UK t: 0141 330 1649 w: http://www.dcs.gla.ac.uk/~srogers e: srogers@dcs.gla.ac.uk s: sdrogersskype