David Tudor Jones (born 1966) is a Professor of Bioinformatics, and Head of Bioinformatics Group in the University College London. He is also the director in Bloomsbury Center for Bioinformatics, which is a joint Research Centre between UCL and Birkbeck, University of London and which also provides bioinformatics training and support services to biomedical researchers. In 2013, he is a member of editorial boards for PLoS ONE, BioData Mining, Advanced Bioinformatics, Chemical Biology & Drug Design, and Protein: Structure, Function and Bioinformatics. Education Jones was educated at Imperial College London where he was awarded a Bachelor of Science degree in Physics. He moved to King's College London to complete a Master of Science degree in Biochemistry followed by University College London where he was awarded a PhD in 1993 for research supervised by William R. Taylor and Janet Thornton. Research and career Jones's main research interests are in protein structure prediction and analysis protein folding, transmembrane protein analysis, machine learning applications in bioinformatics, and genome analysis including the application of intelligent software agents. He has consulted for a few different companies, including GlaxoSmithKline, but his main industry experience was as a co-founder of Inpharmatica Limited, which was founded in 1998 as a corporate spin-off from University College London. The company used a combination of bioinformatics and chemoinformatics to look at the relationships between the structure and function of proteins, and the binding of chemical groups to these proteins leading to the discovery of novel drugs. THREADER THREADER provides a method is popularly known as protein fold recognition (threading), a method of protein modeling, which is used to model those proteins which have the same fold as proteins of known structures. The input is an amino acid sequence with unknown protein structure, then THREADER will output a most probable protein structure for this sequence. The degree of compatibility between the sequence and the proposed structure is evaluated by means of set of empirical potentials derived from proteins of known structures. This work got preceded by David Baker and his colleagues, who have taken THREADER idea further in the form of the Rosetta method which has a huge impact in the field. MEMSAT MEMSAT is an approach to predict the positions of transmembrane helix segments based on the recognition of the topological models of proteins. The method uses a set of statistical tables derived from well-characterized membrane protein data, and we have