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 and methods for RNA-sequencing data analysis. For the time series, an important focus is in developing models of gene regulation using gene expression time series, with application to inferring gene regulatory relationships. We are a subgroup of Statistical Machine Learning and Bioinformatics group at HIIT.