The vast expansion of protein sequence databases provides an opportunity for new protein
design approaches which seek to learn the sequence-function relationship directly from …

Epigenetic modifications are dynamic mechanisms involved in the regulation of gene
expression. Unlike the DNA sequence, epigenetic patterns vary not only between individuals, but …

Protein domains are fundamental units of protein structure and play a pivotal role in
understanding folding, function, evolution, and design. The advent of accurate structure prediction …

The integrative analysis of high‐throughput reporter assays, machine learning, and profiles
of epigenomic chromatin state in a broad array of cells and tissues has the potential to …

Energy-Based Models (EBMs) offer a versatile framework for modelling complex data
distributions. However, training and sampling from EBMs continue to pose significant challenges. …

Recently a number of works have demonstrated successful applications of a fully data-driven
approach to protein design, based on learning generative models of the distribution of a …

A promising alternative to comprehensively performing genomics experiments is to, instead,
perform a subset of experiments and use computational methods to impute the remainder. …

Epigenetic modifications are dynamic control mechanisms involved in the regulation of gene
expression. Unlike the DNA sequence itself, they vary not only between individuals but also …

State-of-the-art methods for the prediction of the structures of interacting protein complexes
rely on the construction of paired multiple sequence alignments, whose rows contain …

With the increasing application of deep learning methods to the modelling of regulatory DNA
sequences has come an interest in exploring what types of architecture are best suited to …