Date: Saturday September 3 – Sunday September 4, 2016 Sponsored by:
Time: 09:00 – 17:00
Venue: World Forum, room: Kilimanjaro 1/2
Contact organisers through: email@example.com
Biology is rapidly turning into an information science, thanks to enormous advances in the ability to observe the molecular properties of cells, organs and individuals. This wealth of data allows us to model molecular systems at an unprecedented level of detail and to start to understand the underlying biological mechanisms. This field of systems biology creates a huge need for methods from machine learning, which find statistical dependencies and patterns in these large-scale datasets and that use them to establish models of complex molecular systems. MLSB is a scientific forum for the exchange between researchers from Systems Biology and Machine Learning, to promote the exchange of ideas, interactions and collaborations between these communities.
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.
Methods: Active learning/Experimental design, Bayesian Methods, Clustering/Biclustering, Data integration/fusion/multi-view learning, Feature/subspace selection, Graph inference/completion, Kernel Methods, Machine Learning Algorithms, Multitask/Structured output prediction, Probabilistic inference, Semi-supervised learning, Systems identification, Time-series analysis
Applications: Biomarker identification, Epigenetics, Genome-wide association studies, Metabolic modeling and reconstruction, Metabolomics, Protein function and structure prediction, Protein-protein interaction networks, Rational drug design methods, Regulatory genomics, Sequence Annotation, Signaling networks, Synthetic biology
Poster abstracts can be submitted until August 19. The poster should be preferably of size A0 in portrait orientation (84.1 x 118.9cm ; or 33.1 x 46.8 inches).
In addition, we will organise a poster pitching session, where you have the opportunity to give a 2 minute oral presentation of your poster.
Abstract of your poster will appear in an informal abstract book that will be available online (unless you instruct otherwise). The abstract should have length 1-2 pages (in arbitrary format).
We encourage submissions bringing forward methods for discovering complex structures (e.g. interaction networks, molecule structures), statistical machine learning methods for analysis of various high-throughput omics data, and methods supporting systems-level data analysis. The submissions are organized into the following two tracks:
Submissions will be evaluated by at least three reviewers from an international programme committee of experts in the field. The most relevant and most original submissions will be accepted as full oral presentations and/or as poster presentations at the workshop.
Submission is through the Easychair system
Registration via the general ECCB2016 registration.
All the organizers
Antti Airola, University of Turku
Chloé-Agathe Azencott, Mines ParisTech/Institut Curie INSERM
Alexis Battle, Johns Hopkins University
Michael A. Beer, Johns Hopkins University
Andreas Beyer, University of Cologne
Céline Brouard, Aalto university
Karsten Borgwardt, ETH Zurich
Gal Chechik, Bar Ilan University
Chao Cheng, Dartmouth Medical School
Manfred Claassen, ETH Zurich
Florence D’Alché-buc, Télécom ParisTech/Institut Mines-Télécom
Saso Dzeroski, Jozef Stefan Institute
Pierre Geurts, University of Liège
Markus Heinonen, Aalto University
James Hensman, Lancaster University
Lars Kaderali, University Medicine Greifswald
David Knowles, Cambridge University
Stefan Kramer, University of Mainz
Anshul Kundaje, Stanford University
François Laviolette, Université Laval
Christina Leslie, Memorial Sloan-Kettering Cancer Center
Hiroshi Mamitsuka, Kyoto University
Martin Renqiang Min, NEC Labs America
Yves Moreau, KU Leuven
Alan Moses, University of Toronto
Sara Mostafavi, UBC
Bernard Ng, University of British Columbia
Mahesan Niranjan, University of Southampton
William Noble, University of Washington
Uwe Ohler, Max Delbrueck Center & Humboldt University
Tapio Pahikkala, University of Turku
Nico Pfeifer, Max Planck Institute for Informatics
Gerald Quon, University of California, Davis
Magnus Rattray, University of Manchester
Yvan Saeys, Ghent University
Guido Sanguinetti, University of Edinburgh
Li Shen, Icahn School of Medicine at Mount Sinai
Motoki Shiga, Gifu University
Oliver Stegle, EMBL-European Bioinformatics Institute
Koji Tsuda, The University of Tokyo
Giorgio Valentini, Universita’ degli Studi di Milano
Jinbo Xu, Toyota Technological Institute at Chicago