Professor David Jones is a preeminent computational biologist whose pioneering work has revolutionized the field of protein structure prediction and analysis. He currently serves as Professor of Bioinformatics and Head of the Bioinformatics Group at University College London, holding dual appointments in the Department of Computer Science and Division of Biosciences. Additionally, he directs the Bloomsbury Center for Bioinformatics, a collaborative research center between UCL and Birkbeck that provides essential training and support services to biomedical researchers across London. His distinguished academic journey began with a Bachelor of Science degree in Physics from Imperial College London, followed by a Master of Science in Biochemistry from King's College London, culminating in a PhD from University College London in 1993 under the supervision of William R. Taylor and Janet Thornton.
Professor Jones has made seminal contributions to computational biology through the development of statistical algorithms that address fundamental problems in protein structure, function, and evolution. His creation of the first protein threading method, THREADER, established a foundational approach that has influenced subsequent protein structure modeling techniques for decades. Perhaps his most widely recognized contribution is PSIPRED, a web portal launched in 1998 that has been utilized nearly two million times by researchers worldwide for predicting protein structure and function from amino acid sequences. His laboratory has produced numerous essential open-source software tools including GenTHREADER, MEMSAT, and DISOPRED, which have become indispensable resources for the global protein research community, enabling significant advances in structural biology and drug discovery.
Beyond his technical contributions, Professor Jones has played a pivotal role in shaping the bioinformatics landscape through his leadership and mentorship. As a Fellow of the Royal Society and the International Society for Computational Biology, he has significantly influenced research directions and standards in computational biology. His editorial roles with prestigious journals including PLoS ONE, BioData Mining, and Protein Structure Function and Bioinformatics have helped guide scholarly discourse in the field. Currently, his research group is expanding into high throughput computing and large-scale machine learning applications for bioinformatics, with particular focus on predicting protein disorder, analyzing expression data, and understanding protein-protein interactions through deep learning techniques. His ongoing work continues to push the boundaries of computational biology, maintaining his position at the forefront of a rapidly evolving scientific discipline that bridges computer science, molecular biology, and structural biology.
