David Jones

Professor of Bioinformatics


Based at UCL

Personal Website


My main research interests are in protein structure prediction and analysis, simulations of protein folding, Hidden Markov Model methods, transmembrane protein analysis, machine learning applications in bioinformatics, de novo protein design methodology, and genome analysis including the application of intelligent software agents. New areas of research include the use of high throughput computing and very large scale machine learning for bioinformatics applications, analysis and prediction of protein disorder, expression data analysis and the analysis and prediction of protein function and protein-protein interactions using deep learning techniques. Over the years I have authored a number of widely-used bioinformatics tools such as PSIPRED, GenTHREADER, MEMSAT and DISOPRED.

Selected publications

FFPred 3: feature-based function prediction for all Gene Ontology domains
Cozzetto, D., Minneci, F., Currant, H., Jones, D.T.
 (2016) 6:31865
DISOPRED3: precise disordered region predictions with annotated protein-binding activity
Jones, D.T., Cozzetto, D.
 (2015) 31 (6):857-863
Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis
Nugent, T., Jones, D.T.