Professor Michael J. E. Sternberg is the Director of the Centre for Integrative Systems Biology and Bioinformatics (CISBIO) and holds the Chair of Structural Bioinformatics.
CISBIO brings together scientists from a wide range of different fields to develop innovative interdisciplinary approaches to understanding biological problems. A key component of the interdisciplinary strategy is a repeated cycle of experimentation and modelling.
Professor Sternberg has been involved in schools outreach programmes funded by the Royal Society and Rolls Royce.
Professor Sternberg entered Bioinformatics via his D.Phil in Biophysics (Oxford). He obtained a first degree in Physics (Cambridge) and a Masters in Computing (Imperial College). He has worked at Oxford, Birkbeck College, Cancer Research UK and joined Imperial College in 2001.
The main research interests of his group are:
- Prediction of protein structure and function
- Prediction of macromolecular docking and interactions
- Prediction of the effect of genetic variants particularlly those associate with disease
- Network modelling for Systems Biology
- Logic-based drug design
Professor Sternberg's group web page is located athttp://www.sbg.bio.ic.ac.uk and includes links to programs and resources available for use by the community.
Full details of his research interests can be found at http://www.sbg.bio.ic.ac.uk/research.html.
et al., 2020, Application of docking methodologies to modeled proteins, Proteins: Structure, Function, and Bioinformatics, Vol:88, ISSN:0887-3585, Pages:1180-1188
Wodak SJ, Velankar S, Sternberg MJE, 2020, Modeling protein interactions and complexes in CAPRI 7th CAPRI evaluation meeting April 3-5 EMBL-EBI, Hinxton UK., Proteins: Structure, Function, and Bioinformatics, Vol:88, ISSN:0887-3585, Pages:913-915
et al., 2020, LGR4 deficiency results in delayed puberty through impaired Wnt/β-catenin signaling, Jci Insight, Vol:5, ISSN:2379-3708, Pages:1-17
Lenhard B, Sternberg MJE, 2020, Computational Resources for Molecular Biology: Special Issue 2020, Journal of Molecular Biology, Vol:432, ISSN:0022-2836, Pages:3361-3363
David A, 2020, A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin, Molecular Genetics and Genomic Medicine, Vol:8, ISSN:2324-9269, Pages:1-9