No ratings yet
Taught by or worked with Simon? Your rating helps other students choose.
Professor Simon Lovell holds a BSc from the University of Bath (1988-1992) and a PhD from the University of Bristol (1992-1995). His early career included a lectureship at the University of Bath (1995-1996), followed by a postdoctoral research associate position at Duke University in North Carolina, USA (1996-2001). He then served as a research fellow at the University of Cambridge (2001-2003) before joining the University of Manchester as a lecturer in 2003. He progressed to senior lecturer in 2007 and was appointed professor in 2012. He currently serves as Associate Dean (Knowledge & Understand) in FBMH Platform Sciences, Enabling Technologies & Infrastructure, and as Professor of Molecular Biology in the Division of Evolution, Infection and Genomics within the School of Biological Sciences at the Faculty of Biology, Medicine and Health.
Professor Lovell’s research focuses on understanding the three-dimensional structure of proteins through computational methods. His work examines sequence-structure relationships, exploring how linear amino acid sequences determine protein folding and function. He investigates evolutionary aspects of protein structure, noting that structure is generally more conserved than sequence due to functional constraints, and applies this to predict structure and understand evolutionary changes. Additionally, his research addresses protein function by identifying functional sites, binding sites, and protein-protein interaction sites using knowledge of structure and evolutionary restraints. This approach aids in interpreting data from genome-sequencing and structural genomics projects. He contributes to the Digital Futures and Lydia Becker Institute research beacons and aligns with UN Sustainable Development Goals related to good health and well-being and life on land. His verified professional email is not publicly listed on official university profiles.
A new genetic study from University of Manchester reveals structural limits on SARS-CoV-2 evolution, explaining variant patterns and guiding vaccine strategies.
Photo by Antoine Dautry on Unsplash
Photo by Chris Liverani on Unsplash
Photo by Peter Burdon on Unsplash
Photo by Andrii Zhuk on Unsplash
Photo by EESOFUFFZICH on Unsplash
Photo by Google DeepMind on Unsplash
Photo by Gabriele Malaspina on Unsplash
