Mike Sternberg | |
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Born | Michael Joseph Ezra Sternberg 24 June 1951 [1] |
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Scientific career | |
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Thesis | Studies of Protein Conformation (1977) |
Doctoral advisor | David Chilton Phillips [3] |
Website | www |
Michael Joseph Ezra Sternberg (born 24 June 1951) [1] is a professor at Imperial College London, where he is director of the Centre for Integrative Systems Biology and Bioinformatics [4] and Head of the Structural bioinformatics Group. [2] [5] [6] [7]
Sternberg was educated at Hendon County Grammar School and Gonville and Caius College, Cambridge, where he was awarded a Bachelor of Arts degree in natural sciences (theoretical physics) in 1972. [1] He went on to do a Master of Science degree in Computing at Imperial College London followed by a DPhil degree from the University of Oxford (Wolfson College, Oxford) in 1978 for research supervised by David Chilton Phillips. [3] [8] [9] [10] [11] [12]
After postdoctoral research at the University of Oxford, Sternberg became a Lecturer in the Department of Crystallography at Birkbeck College, London. He went on to work at the Imperial Cancer Research Fund and joined Imperial College in 2001. [1] [13] [14] [15] [16] He is the Director of the Centre for Integrative Systems Biology and Bioinformatics [4] at Imperial College.
Sternberg's research interests are in protein structure prediction, protein function prediction, prediction of macromolecular docking and interactions, network modelling for systems biology and logic-based drug design. [13] [17] [18] [19] [20] [21] [22] [23] [24] [25]
He has authored or co-authored several books including From Cells to Atoms: an illustrated introduction to molecular biology, [26] Protein Engineering: a practical approach [27] and Protein Structure Prediction: a practical approach. [28]
During his DPhil research at Oxford he worked with Janet Thornton and they undertook some of the first systematic analyses of protein structure. They identified that the beta-alpha-beta unit in proteins is nearly always right handed and this explained remarkable similarities between protein structures.[ citation needed ]
His group, particularly Lawrence Kelley, have developed the widely used Phyre/Phyre2 web server [29] [30] [31] for protein structure prediction. This web resource has been used by over 100,000 distinct users worldwide.[ citation needed ]
Recently his PhD student Chris Yates developed SuSPect, [32] a novel powerful method to predict the phenotypic effects of Single-nucleotide polymorphisms and other amino acid variants.
Sternberg was elected a Fellow of the Royal Society of Biology (FRSB) and a Fellow of the Institute of Biology (FIBiol). He is an associate editor of the Journal of Molecular Biology .
In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution. Methodologies used include sequence alignment, searches against biological databases, and others.
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; and it is important in medicine and biotechnology.
Sir Thomas Leon Blundell, is a British biochemist, structural biologist, and science administrator. He was a member of the team of Dorothy Hodgkin that solved in 1969 the first structure of a protein hormone, insulin. Blundell has made contributions to the structural biology of polypeptide hormones, growth factors, receptor activation, signal transduction, and DNA double-strand break repair, subjects important in cancer, tuberculosis, and familial diseases. He has developed software for protein modelling and understanding the effects of mutations on protein function, leading to new approaches to structure-guided and Fragment-based lead discovery. In 1999 he co-founded the oncology company Astex Therapeutics, which has moved ten drugs into clinical trials. Blundell has played central roles in restructuring British research councils and, as President of the UK Science Council, in developing professionalism in the practice of science.
Dame Janet Maureen Thornton, is a senior scientist and director emeritus at the European Bioinformatics Institute (EBI), part of the European Molecular Biology Laboratory (EMBL). She is one of the world's leading researchers in structural bioinformatics, using computational methods to understand protein structure and function. She served as director of the EBI from October 2001 to June 2015, and played a key role in ELIXIR.
Protein function prediction methods are techniques that bioinformatics researchers use to assign biological or biochemical roles to proteins. These proteins are usually ones that are poorly studied or predicted based on genomic sequence data. These predictions are often driven by data-intensive computational procedures. Information may come from nucleic acid sequence homology, gene expression profiles, protein domain structures, text mining of publications, phylogenetic profiles, phenotypic profiles, and protein-protein interaction. Protein function is a broad term: the roles of proteins range from catalysis of biochemical reactions to transport to signal transduction, and a single protein may play a role in multiple processes or cellular pathways.
Phyre and Phyre2 are free web-based services for protein structure prediction. Phyre is among the most popular methods for protein structure prediction having been cited over 1500 times. Like other remote homology recognition techniques, it is able to regularly generate reliable protein models when other widely used methods such as PSI-BLAST cannot. Phyre2 has been designed to ensure a user-friendly interface for users inexpert in protein structure prediction methods. Its development is funded by the Biotechnology and Biological Sciences Research Council.
Sean Roberts Eddy is Professor of Molecular & Cellular Biology and of Applied Mathematics at Harvard University. Previously he was based at the Janelia Research Campus from 2006 to 2015 in Virginia. His research interests are in bioinformatics, computational biology and biological sequence analysis. As of 2016 projects include the use of Hidden Markov models in HMMER, Infernal Pfam and Rfam.
Cyrus Homi Chothia was an English biochemist who was an emeritus scientist at the Medical Research Council (MRC) Laboratory of Molecular Biology (LMB) at the University of Cambridge and emeritus fellow of Wolfson College, Cambridge.
David Tudor 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, 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.
Chris Sander is a computational biologist based at the Dana-Farber Cancer Center and Harvard Medical School. Previously he was chair of the Computational Biology Programme at the Memorial Sloan–Kettering Cancer Center in New York City. In 2015, he moved his lab to the Dana–Farber Cancer Institute and the Cell Biology Department at Harvard Medical School.
Burkhard Rost is a scientist leading the Department for Computational Biology & Bioinformatics at the Faculty of Informatics of the Technical University of Munich (TUM). Rost chairs the Study Section Bioinformatics Munich involving the TUM and the Ludwig Maximilian University of Munich (LMU) in Munich. From 2007-2014 Rost was President of the International Society for Computational Biology (ISCB).
A protein superfamily is the largest grouping (clade) of proteins for which common ancestry can be inferred. Usually this common ancestry is inferred from structural alignment and mechanistic similarity, even if no sequence similarity is evident. Sequence homology can then be deduced even if not apparent. Superfamilies typically contain several protein families which show sequence similarity within each family. The term protein clan is commonly used for protease and glycosyl hydrolases superfamilies based on the MEROPS and CAZy classification systems.
Alfonso Valencia is a Spanish biologist, ICREA Professor, current director of the Life Sciences department at Barcelona Supercomputing Center. and of Spanish National Bioinformatics Institute (INB-ISCIII). From 2015-2018, he was President of the International Society for Computational Biology. His research is focused on the study of biomedical systems with computational biology and bioinformatics approaches.
Timothy John Phillip Hubbard is a Professor of Bioinformatics at King's College London, Head of Genome Analysis at Genomics England and Honorary Faculty at the Wellcome Trust Sanger Institute in Cambridge, UK. Starting March 1, 2024, Tim will become the director of Europe's Life Science Data Infrastructure ELIXIR.
Single nucleotide polymorphism annotation is the process of predicting the effect or function of an individual SNP using SNP annotation tools. In SNP annotation the biological information is extracted, collected and displayed in a clear form amenable to query. SNP functional annotation is typically performed based on the available information on nucleic acid and protein sequences.
Julian John Thurstan Gough is a Group Leader in the Laboratory of Molecular Biology (LMB) of the Medical Research Council (MRC). He was previously a professor of bioinformatics at the University of Bristol.
Christine Anne Orengo is a Professor of Bioinformatics at University College London (UCL) known for her work on protein structure, particularly the CATH database. Orengo serves as president of the International Society for Computational Biology (ISCB), the first woman to do so in the history of the society.
Proline-rich protein 30 is a protein in humans that is encoded for by the PRR30 gene. PRR30 is a member in the family of Proline-rich proteins characterized by their intrinsic lack of structure. Copy number variations in the PRR30 gene have been associated with an increased risk for neurofibromatosis.