Annual Report 2013
Probabilistic Mechanistic Models for Genomics
We develop methods for efficient Bayesian inference in complex modelling problems. Our main applications are in developing statistical methods for modelling molecular biology time series using Gaussian processes, as well as methods for RNA-sequencing and metagenomic sequencing data analysis. We are a subgroup of Statistical Machine Learning and Bioinformatics group at HIIT.
YContact person: Academy Research Fellow Antti Honkela
Home page: http://www.hiit.fi/node/2629