Charlotte Deane
Scholar

Charlotte Deane

Google Scholar ID: QAdcBnQAAAAJ
Professor of Structural Bioinformatics, Oxford University
BioinformaticsStructural BioinformaticsProtein evolutionImmunoinformatics
Citations & Impact
All-time
Citations
11,424
 
H-index
53
 
i10-index
175
 
Publications
20
 
Co-authors
37
list available
Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • - Conference Presentations: Since 2014, presented at multiple international conferences such as EBI Biologics, SMBE, Drug Discovery Summit, etc.
  • - Media Appearances: Featured in several video interviews and podcasts discussing topics like the structural antibody database, developability issues affecting therapeutic monoclonal antibodies, loop conformational ensembles, and the role of AI in drug discovery.
Research Experience
  • - Professor, Department of Statistics, University of Oxford (2008-)
  • - Deputy Executive Chair of the Engineering and Physical Sciences Research Council (2019-2021)
  • - Head of Department of Statistics (2015-2019)
  • - Deputy Head of the Mathematical, Physical and Life Sciences (MPLS) Division (2018-2020)
  • - Associate Head (Research) of MPLS Division (2014-2019)
  • - Associate Head (Impact and Innovation) of MPLS Division (2013-2014)
  • - Director - Systems Approaches to Biomedical Science Centre for Doctoral Training (2009-)
  • - Director - Systems Biology Doctoral Training Centre (2007-2009)
  • - University Lecturer, Department of Statistics, University of Oxford (2002-2008)
  • - Welcome Trust Research Fellow, University of California Los Angeles (2000-2002)
Education
  • - PhD: Jesus College, University of Cambridge
  • - MA: Chemistry, University College, University of Oxford
Background
  • - Research Interests: Protein structure prediction, immunoinformatics, biological networks, and small molecule drug discovery
  • - Professional Field: Structural Bioinformatics
  • - Brief Introduction: Leads the Oxford Protein Informatics group, a research group of over 20 people working on diverse problems across protein structure, immunoinformatics, biological networks, and small molecule drug discovery.
Miscellany
  • - Personal Interests: Not explicitly mentioned