David Tudor Jones

David Tudor Jones (born 1966)[1] is a Professor of Bioinformatics, and Head of Bioinformatics Group in the University College London.[3] 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.

David Jones
David Jones in 2006
Born
David Tudor Jones

November 1966 (age 53)[1]
NationalityBritish
Alma mater
Known forProtein Fold Recognition
Protein Structure Prediction
AwardsRoyal Society University Research Fellowship (1995-1999)
Scientific career
Fields
InstitutionsUniversity College London
Birkbeck, University of London
ThesisStructural approaches to protein sequence analysis (1993)
Doctoral advisor
Websitehttp://www.cs.ucl.ac.uk/staff/d.jones/

Education

Jones was educated at Imperial College London where he was awarded a Bachelor of Science degree in Physics. Me 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[4] for research supervised by William R. Taylor and Janet Thornton.

Research and career

Jones's main research interests[2] 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.[5] He has consulted for a few different companies, including GlaxoSmithKline, but his main industry experience was as a co-founder of Inpharmatica Limited,[1] 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[6] 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[7] 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,[8] 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 database

Jones was involved in the early stage of development of the CATH database, with Christine Orengo and Janet Thornton[9] 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. The CATH database employs a combination of automatic and manual techniques.[10][11]

GenTHREADER

GenTHREADER[12] 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.[13] So far, there are several improved methods available now: mGenTHREADER, pDomTHREADER, and pGenTHREADER.[14] [15]

PSIPRED

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.[16]

Academic service

Since 1996, Jones has been involved in many research committees, including: Biotechnology and Biological Sciences Research Council (BBSRC), Engineering and Physical Sciences Research Council (EPSRC), Medical Research Council (MRC), and Research Councils UK. His research has been funded by the BBSRC, The Wellcome Trust, Elsevier, the EPSRC, the MRC, The Royal Society, The European Commission, AstraZeneca, GlaxoSmithKline and Sun Microsystems.[3]

Awards and honours

Jones held a prestigious Royal Society University Research Fellowship from 1995 to 1999.[3]

gollark: 100
gollark: Maybe it's a camera configuration thing.
gollark: Interesting.
gollark: Do you look like a potato when you are alone in a photo?
gollark: ++magic py `return "bees"`

References
  1. n (2012). "David JONES Inpharmatica". companieshouse.gov.uk. Companies House. Archived from the original on 2017-03-07.
  2. David Tudor Jones publications indexed by Google Scholar
  3. Jones, David (2015). "Professor David Jones UCL Computer Science". ucl.ac.uk. University College London. Archived from the original on 2016-05-07.
  4. Jones, David Tudor (1993). Structural approaches to protein sequence analysis. london.ac.uk (PhD thesis). University of London. OCLC 941025790.
  5. Jones, David T.; Taylor, William R.; Thornton, Janet M. (1992). "The rapid generation of mutation data matrices from protein sequences". Bioinformatics. 8 (3): 275–282. doi:10.1093/bioinformatics/8.3.275. ISSN 1367-4803. PMID 1633570.
  6. Jones, D. T.; Taylor, W. R.; Thornton, J. M. (1992). "A new approach to protein fold recognition". Nature. 358 (6381): 86–89. doi:10.1038/358086a0. ISSN 0028-0836. PMID 1614539.
  7. 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 (10): 3038–3049. doi:10.1021/bi00176a037. ISSN 0006-2960. PMID 8130217.
  8. Jones, D. T. (2007). "Improving the accuracy of transmembrane protein topology prediction using evolutionary information". Bioinformatics. 23 (5): 538–544. doi:10.1093/bioinformatics/btl677. ISSN 1367-4803. PMID 17237066.
  9. Orengo, CA; Michie, AD; Jones, S; Jones, DT; Swindells, MB; Thornton, JM (1997). "CATH – a hierarchic classification of protein domain structures". Structure. 5 (8): 1093–1109. doi:10.1016/S0969-2126(97)00260-8. ISSN 0969-2126. PMID 9309224.
  10. 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 (6): 1155–1167. doi:10.1107/s0907444998007501. PMID 10089492.
  11. Cuff, A. L.; Sillitoe, I.; Lewis, T.; Clegg, A. B.; Rentzsch, R.; Furnham, N.; Pellegrini-Calace, M.; Jones, D.; Thornton, J.; Orengo, C. A. (2010). "Extending CATH: increasing coverage of the protein structure universe and linking structure with function". Nucleic Acids Research. 39 (Database): D420–D426. doi:10.1093/nar/gkq1001. ISSN 0305-1048. PMC 3013636. PMID 21097779.
  12. Jones, David T. (1999). "GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences". Journal of Molecular Biology. 287 (4): 797–815. doi:10.1006/jmbi.1999.2583. ISSN 0022-2836. PMID 10191147. S2CID 6057225.
  13. "UCL-CS Bioinformatics: PSIPRED overview". Bioinf.cs.ucl.ac.uk. Retrieved 2017-03-07.
  14. McGuffin, L. J.; Jones, D. T. (2003). "Improvement of the GenTHREADER method for genomic fold recognition". Bioinformatics. 19 (7): 874–881. doi:10.1093/bioinformatics/btg097. ISSN 1367-4803. PMID 12724298.
  15. Lobley, A.; Sadowski, M. I.; Jones, D. T. (2009). "pGenTHREADER and pDomTHREADER: new methods for improved protein fold recognition and superfamily discrimination". Bioinformatics. 25 (14): 1761–1767. doi:10.1093/bioinformatics/btp302. ISSN 1367-4803. PMID 19429599.
  16. McGuffin, L. J.; Bryson, K.; Jones, D. T. (2000). "The PSIPRED protein structure prediction server". Bioinformatics. 16 (4): 404–405. doi:10.1093/bioinformatics/16.4.404. ISSN 1367-4803. PMID 10869041.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.