The expanding scale and inherent complexity of biological data have encouraged a
growing use of machine learning in biology to build informative and predictive models of the …

Allostery is the functional change at one site on a protein caused by a change at a distant site.
In order for the benefits of allostery to be taken advantage of, both for basic understanding …

Although many structural bioinformatics tools have been using neural network models for a
long time, deep neural network (DNN) models have attracted considerable interest in recent …

The inapplicability of amino acid covariation methods to small protein families has limited
their use for structural annotation of whole genomes. Recently, deep learning has shown …

The design of novel proteins has many applications but remains an attritional process with
success in isolated cases. Meanwhile, deep learning technologies have exploded in …

In this article, we describe our efforts in contact prediction in the CASP13 experiment. We
employed a new deep learning‐based contact prediction tool, DeepMetaPSICOV (or DMP for …

Background Despite being hugely important in biological processes, allostery is poorly
understood and no universal mechanism has been discovered. Allosteric drugs are a largely …

Deep learning-based prediction of protein structure usually begins by constructing a multiple
sequence alignment (MSA) containing homologs of the target protein. The most successful …

Cysteine‐reactive small molecules are used as chemical probes of biological systems and
as medicines. Identifying high‐quality covalent ligands requires comprehensive kinetic …

Major computational challenges exist in relation to the collection, curation, processing and
analysis of large genomic and imaging datasets, as well as the simulation of larger and more …