MLSB17, the Eleventh International Workshop on Machine Learning in Systems Biology will take place as a Special Session at ISMB/ECCB 2017 in Prague, Czech Republic, on July 25, 2017.

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.

Summary

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.


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
Active learning/experimental design Biomarker identification
Bayesian methods Epigenetics
Clustering/biclustering Genome-wide association studies
Data integration/fusion/multi-view learning Metabolic modeling and reconstruction
Deep learning Metabolomics
Feature/subspace selection Precision medicine
Graph inference/completion Protein function and structure prediction
Kernel methods Protein-protein interaction networks
Machine learning algorithms Rational drug design
Multitask/structured output prediction Regulatory genomics
Probabilistic inference Sequence annotation
Semi-supervised learning Signaling networks
Systems identification Synthetic biology
Time-series analysis Transcriptomics

 

MLSB17 Chairs

Chloé-Agathe Azencott MINES ParisTech and Institut Curie, Paris, France
Magnus Rattray University of Manchester, UK

 

Scientific Program Committee 2017

Currently being formed.

 

Contact

For further information, please contact the Chairs.