The increasing sophistication of high-throughput molecular technologies offers exciting possibilities for systems-level analysis of biological systems. Yet such novel and diverse data are frequently accompanied by significant statistical and computational challenges.
This meeting aims to bring together researchers operating at the interface of systems biology, mathematical modelling and statistics, in order to better leverage emerging data using state-of-the-art statistical methodologies.
In partnership with Statistical Applications in Genetics and Molecular Biology (De Gruyter) we are soliciting high-quality research articles for joint journal submission and presentation at the workshop. In addition, we are encouraging the submission of contributed presentations and posters in relevant research areas.
Themes for this workshop include, but are not limited to,
- data-driven models for cellular signalling and information processing
- novel analysis of advanced sequencing data
- models for single cell imaging data
- kinetic models; advances in parameter estimation and structure learning
- integration of multiple heterogeneous data sources
- network analysis for multivariate biological data
- models for cellular stochasticity
- advances in normalisation and testing for high-throughput data
|Prof. Nigel Burroughs, Mathematics Institute and Systems Biology Centre, Warwick.|
|Dr. Ramon Grima, Reader in Stochastic Systems Biology, Edinburgh.|
|Prof. Mustafa Khammash, Control Theory and Systems Biology, ETH Zurich.|
|Prof. Walter Kolch, Director of Systems Biology Ireland and Director of the Conway Institute, University College Dublin.|
|Prof. John Lygeros, Head of the Automatic Control Laboratory, ETH Zurich.|
|Dr. Sach Mukherjee, Programme Leader at the MRC Biostatistics Unit, Cambridge.|
|Prof. David Rand, Director of the Systems Biology Centre, Warwick.|
|Prof. Darren Wilkinson, School of Mathematics and Statistics, Newcastle.|
in partnership with