News

G3 paper

Our paper “Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders” has been published in G3. In this paper we analyse the mathematical structure of a class of statistical models for learning hidden factors influencing gene expression data and show that a new algorithm based on the …

Congrats Ammar!

Congratulations to Ammar, whose paper “High-dimensional multi-trait GWAS by reverse prediction of genotypes” has been accepted for presentation at CIBB 2021!

Congrats Ramin!

Congratulations to Ramin, whose paper “A graph feature auto-encoder for the prediction of unobserved node features on biological networks” has been published in BMC Bioinformatics!