iPMCMC for Cancer Progression

Dnr:

SNIC 2017/1-312

Type:

SNAC Medium

Principal Investigator:

Jens Lagergren

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2017-07-10

End Date:

2018-08-01

Primary Classification:

10610: Bioinformatik och systembiologi (metodutveckling under 10203)

Webpage:

Allocation

Abstract

The Project is concerned with Machine Learning and probabilistic modeling applied to cancer, in particular somatic evolution in cancer and cancer heterogeneity. Methodologically, this project is focused on Sequential Markov Chain, Interacting Particle Markov Chain Monte Carlo (iPMCMC) as well as implementation of such methods on modern high performance computers and clusters. We collaborate with Swedish groups developing new experimental methods and data at SciLifeLab as well as with international collaborators, e.g., Shah Lab for Computational Cancer Biology at the British Colombia Cancer Research Center.