MLSB14, the Eighth International Workshop on Machine Learning in Systems Biology will take place in conjunction with ECCB in Strasbourg, France on Sept 6-7, 2014.

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 program is now available

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.

Topics

We encourage submissions bringing forward methods for discovering complex structures (e.g. interaction networks, molecule structures) and methods supporting genome-wide data analysis. A non-exhaustive list of topics suitable for this workshop are:

Methods Applications
Machine Learning Algorithms Sequence Annotation
Bayesian Methods Gene Expression and post-transcriptional regulation
Data integration/fusion Inference of gene regulation networks
Graphical models and causality Metagenomics
Feature/subspace selection Gene prediction and whole genome association studies
Clustering Metabolic pathway modeling
Biclustering/association rules Signaling networks
Kernel Methods Systems biology approaches to biomarker identification
Probabilistic inference Rational drug design methods
Structured output prediction Metabolic reconstruction
Systems identification Protein function and structure prediction
Graph inference, completion, smoothing Protein-protein interaction networks
Semi-supervised learning Synthetic biology

 

MLSB14 Chairs

Florence d'Alché-Buc IBISC, Université d'Evry, Genopole, France and LRI, Université Paris Sud, France
Pierre Geurts University of Liege, Institut Montefiore, Liege, Belgium

 

Scientific Program Committee 2014


Florence d'Alché-Buc (University of Evry, France)
Chloé-Agathe Azencott (CBIO, Mines ParisTech, Institut Curie, INSERM, France)
Karsten Borgwardt (MPI Tubingen, Germany)
Sašo Džeroski (Jožef Stefan Institute, Slovenia)
Mohamed Elati (Universite d'Evry, France)
Pierre Geurts (University of Liège, Belgium)
Markus Heinonen (University of Evry, France)
Van Anh Huynh-Thu (University of Edinburgh, UK)
Ross King (Aberystwyth University, UK)
Stefan Kramer (University of Mainz, Germany)
Yves Moreau (Katholieke Universiteit Leuven, Belgium)
Sach Mukherjee (Netherlands Cancer Institute, Netherlands)
Mahesan Niranjan (University of Southampton, UK)
Uwe Ohler (Duke University, USA)
John Pinney (Imperial College London, UK)
Simon Rogers (University of Glasgow, UK)
Juho Rousu (Aalto University, Finland)
Yvan Saeys (University of Ghent, Belgium)
Peter Sykacek (BOKU University, Austria)
Nizar Touleimat (Centre National de Genotypage, CEA, France)
Koji Tsuda (National Institute of Advanced Industrial Science and Technology, Japan)
Jean-Philippe Vert (Ecole des Mines de Paris, France)
Filip Zelezny (Czech Technical University in Prague, Czech Republic)

Local Organizing Committee

Florence d'Alché-Buc (University of Evry, France)
Pierre Geurts (University of Liege, Belgium)
Markus Heinonen (University of Evry, France)
Van Anh Huynh-Thu (University of Edinburgh, UK)
Nizar Touleimat (Centre National de Genotypage, Genopole, Evry)

Contact

For further information, please contact chairsmlsb2014@gmail.com