Apologies for multiple postings: ************************** Call for Posters ***************************** MLSB 2010 The Fourth International Workshop on Machine Learning in Systems Biology 15-16 October 2010, Edinburgh, Scotland *********************************************************************** http://mlsb10.ijs.si/ **REGISTRATION IS NOW OPEN** 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/). POSTER SUBMISSION INSTRUCTIONS We invite you to submit an extended abstract of at least 1 page 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 KEY DATES Poster submission deadline: September 30th 2010 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 -- Dr Simon Rogers Lecturer in Inference School of Computing Science University of Glasgow simon.rogers@glasgow.ac.uk skype: sdrogersskype The University of Glasgow, charity number SC004401