User profiles for J. G. Greener
Joe G GreenerGroup leader, MRC LMB Verified email at mrc-lmb.cam.ac.uk Cited by 1730 |
A guide to machine learning for biologists
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 …
growing use of machine learning in biology to build informative and predictive models of the …
[HTML][HTML] Structure-based prediction of protein allostery
JG Greener, MJE Sternberg - Current Opinion in Structural Biology, 2018 - Elsevier
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 …
In order for the benefits of allostery to be taken advantage of, both for basic understanding …
Recent developments in deep learning applied to protein structure prediction
SM Kandathil, JG Greener… - … : Structure, Function, and …, 2019 - Wiley Online Library
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 …
long time, deep neural network (DNN) models have attracted considerable interest in recent …
[HTML][HTML] Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints
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 …
their use for structural annotation of whole genomes. Recently, deep learning has shown …
[HTML][HTML] Design of metalloproteins and novel protein folds using variational autoencoders
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 …
success in isolated cases. Meanwhile, deep learning technologies have exploded in …
Prediction of interresidue contacts with DeepMetaPSICOV in CASP13
SM Kandathil, JG Greener… - … : Structure, Function, and …, 2019 - Wiley Online Library
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 …
employed a new deep learning‐based contact prediction tool, DeepMetaPSICOV (or DMP for …
[HTML][HTML] AlloPred: prediction of allosteric pockets on proteins using normal mode perturbation analysis
JG Greener, MJE Sternberg - BMC bioinformatics, 2015 - Springer
Background Despite being hugely important in biological processes, allostery is poorly
understood and no universal mechanism has been discovered. Allosteric drugs are a largely …
understood and no universal mechanism has been discovered. Allosteric drugs are a largely …
Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins
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 …
sequence alignment (MSA) containing homologs of the target protein. The most successful …
High‐Throughput Kinetic Analysis for Target‐Directed Covalent Ligand Discovery
…, CE Allen, S Matthies, JG Greener… - Angewandte Chemie …, 2018 - Wiley Online Library
Cysteine‐reactive small molecules are used as chemical probes of biological systems and
as medicines. Identifying high‐quality covalent ligands requires comprehensive kinetic …
as medicines. Identifying high‐quality covalent ligands requires comprehensive kinetic …
[HTML][HTML] Julia for biologists
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 …
analysis of large genomic and imaging datasets, as well as the simulation of larger and more …