MLSB 2010 – call for posters/registration

******************* Call for Posters/Registration **********************

MLSB 2010

The Fourth International Workshop on Machine Learning in Systems Biology

15-16 October 2010, Edinburgh, Scotland


(apologies for multiple postings)



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

The Workshop is organized as “core – event” of Pattern Analysis,
Statistical Modelling and Computational Learning – Network of Excellence
2 (PASCAL 2,


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.


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,


We invite you to submit an abstract of up to 4 pages (minimum 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:


30th September: Poster submission deadline.


A non-exhaustive list of topics suitable for this workshop is given


Machine learning algorithms
Bayesian methods
Data integration/fusion
Feature/subspace selection
Biclustering/association rules
Kernel methods
Probabilistic inference
Structured output prediction
Systems identification
Graph inference, completion, smoothing
Semi-supervised learning


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


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


Saöo Dûeroski, Jozef Stefan Institute, Ljubljana, Slovenia
Simon Rogers, University of Glasgow, UK
Guido Sanguinetti, University of Sheffield/University of Edinburgh, UK


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


Fiona Clark, University of Edinburgh, UK
Dragi Kocev, Jozef Stefan Institute, Ljubljana, Slovenia (webmaster)

Dr Simon Rogers
Lecturer in Inference
School of Computing Science
University of Glasgow (at)
skype: sdrogersskype