David Tudor Jones

David T. Jones
Residence London, UK
Citizenship UK
Nationality UK
Fields Bioinformatics
Computational Biology
Institutions University College London
Alma mater University College London
PhD, Bioinformatics (1988)

King's College London
M.Sc., Biochemistry (1989)

Imperial College London
B.Sc., Physics (1993)
Doctoral advisor Willie Taylor
Janet Thornton
Known for Protein Fold Recognition
Protein Structure Prediction
Notable awards Royal Society University Research Fellowship (1995-1999)
Website
http://www.cs.ucl.ac.uk/staff/d.jones/

David T. Jones 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 College 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.

Biography

Since 1996, Professor Jones has been involved in many research committees, including: Biotechnology and Biological Sciences Research Council, Engineering and Physical Sciences Research Council, Medical Research Council, and Research Council UK.
Professor 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 GSK, but his main industry experience was as a co-founder of Inpharmatica Ltd., which was founded in 1998 as a spin-out company 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.

Research achievements

THREADER (1991)

This method THREADER [1] 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(1994)

This MEMSAT [2] 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 a dynamic programming algorithm to recognize the membrane topology models by maximizing the expectation.
Since MEMSAT was originally built back in 1994, it then triggered a lot of improvements in the prediction of secondary structure. The newest version is MEMSAT3,[3] released in 2007. It uses a neural network to determine the locations of residues are on the cytoplasmic side of the membrane or in the transmembrane helices.

CATH (1997)

Prof Jones was involved in the early stage of development of CATH database,[4] which is a hierarchical domain classification of protein structures in the Protein Data Bank, where the 4 major levels in hierarchy are: Class, Architecture, Topology, and Homologous superfamily. In CATH database employs a combination of automatic and manual techniques.[5][6]

GenTHREADER (1999)

GenTHREADER[7] is a faster and more powerful tool for protein fold recognition, that can be applied to either whole/individual protein sequences.
The method uses a traditional sequence alignment algorithm to generate alignments, and then the alignment will be evaluated by threading techniques. As the last step, each model will be evaluated by a neural network to produce a measurement of the confidence level in the proposed prediction.
The emergence of GenTHREADER has enabled a series of improvement work. So far, there are several improved methods available now: mGenTHREADER, pDomTHREADER, and pGenTHREADER.[8][9]

PSIPRED Protein Structure Prediction Server (1999)

This is a server that aggregates several structure prediction methods. It includes the newly implemented method also known as PSIPRED (Predict Secondary Protein Structure), a technique for protein secondary structure prediction, and the other techniques Predict Transmembrane Topology (MEMSAT3), and Fold Recognition (GenTHREADER). Users submit a protein sequence, perform any prediction of interest, and receive the results by e-mail.[10][11]

References

  1. ↑ Jones, D.T., Taylor, W.R. & Thornton, J.M. (1992) A new approach to protein fold recognition. Nature 358, 86-89.
  2. ↑ Jones, D.T., Taylor, W.R. & Thornton, J.M. (1994) A model recognition approach to the prediction of all-helical membrane protein structure and topology. Biochemistry. 33, 3038-3048.
  3. ↑ Jones, D.T. (2007) Improving the accuracy of transmembrane protein topology prediction using evolutionary information. Bioinformatics. 23, 538-544.
  4. ↑ Orengo, C.A., Michie, A.D., Jones, S., Jones, D.T., Swindells, M.B. & Thornton. J.M. (1997) CATH - a hierarchic classification of protein domain structures. Structure. 5, 1093-1108.
  5. ↑ Orengo, C.A., Martin, A.M., Hutchinson, G., Jones, S., Jones, D.T., Michie, A.D., Swindells, M.B. & Thornton, J.M. (1998) Classifying a protein in the CATH database of domain structures. Acta Crystallogr. D. 54, 1155-1167.
  6. ↑ Cuff, A.L., Sillitoe, I., Lewis, T., Clegg, A.B., Rentzsch, R,, Furnham, N., Pellegrini-Calace, M., Jones, D., Thornton, J. & Orengo, C.A. (2011) Extending CATH: increasing coverage of the protein structure universe and linking structure with function. Nucl. Acids Res. 39, D420-D426.
  7. ↑ Jones, D.T. (1999) GenTHREADER: An efficient and reliable protein fold recognition method for genomic sequences. J. Mol. Biol. 287, 797-815.
  8. ↑ McGuffin, L.J. & Jones, D.T. (2003) Improvement of the GenTHREADER method for genomic fold recognition. Bioinformatics, 19, 874-881.
  9. ↑ Lobley, A., Sadowski, M.I. & Jones, D.T. (2009) pGenTHREADER and pDomTHREADER: New Methods For Improved Protein Fold Recognition and Superfamily Discrimination. Bioinformatics. 25, 1761-1767.
  10. ↑ PSIPRED
  11. ↑ McGuffin L.J., Bryson K., Jones, D.T. (2000) The PSIPRED protein structure prediction server. Bioinformatics. 16, 404-405.

External links

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