Predicting the best treatment strategy from genomic information is a core goal of precision
medicine. Here we focus on predicting drug response based on a cohort of genomic, …

Motivation: High-throughput sequencing enables expression analysis at the level of individual
transcripts. The analysis of transcriptome expression levels and differential expression (DE…

Bacterial genomes vary extensively in terms of both gene content and gene sequence. This
plasticity hampers the use of traditional SNP-based methods for identifying all genetic …

Variational Bayesian (VB) methods are typically only applied to models in the conjugate-exponential
family using the variational Bayesian expectation maximisation (VB EM) algorithm …

Differentially private (DP) machine learning has recently become popular. The privacy loss
of DP algorithms is commonly reported using (ed)-DP. In this paper, we propose a numerical …

We present a computational method for identifying potential targets of a transcription factor (TF)
using wild-type gene expression time series data. For each putative target gene we fit a …

Motivation: Inference of latent chemical species in biochemical interaction networks is a key
problem in estimation of the structure and parameters of the genetic, metabolic and protein …

Genes with similar transcriptional activation kinetics can display very different temporal
mRNA profiles because of differences in transcription time, degradation rate, and RNA-…

In this chapter, a non-linear extension to independent component analysis is developed.
The non-linear mapping from source signals to observations is modelled by a multi-layer …

Opportunistic bacterial pathogen species and their strains that colonise the human gut are
generally understood to compete against both each other and the commensal species …