Contact information
Websites
-
Marsden Group | Research Informatics
Research Group, Kennedy Institute
-
CMD Research Informatics
Research group
Brian Marsden
BA (Cantab), MA (Cantab), D.Phil. (Oxon)
Associate Professor, Research Informatics; Associate Head of Medical Sciences Division - Digital and Information
- Chair of University Research Computing Board
Brian is responsible for driving research informatics and research computing capabilities at the Kennedy Institute and the Centre for Medicines Discovery.
After completing a D.Phil. within the Iain Campbell lab at the University of Oxford, Brian was awarded a Wellcome Trust Prize Fellowship which he spent at the Abagyan lab at the Scripps Research Institute, La Jolla, USA, devising novel methods for proteins structure superimposition and also implementing high performance compute and storage clusters. He then worked as part of the Computational Chemistry group at BioFocus PLC before settling down at the SGC in Oxford and now the Centre for Medicines Discovery where he continues to be responsible for all aspects of Informatics, IT and structural bioinformatics. He has a particular interest in the development of novel data capture and visualisation methods for structural and chemical biology data.
Since 2013, Brian has split his time with the Kennedy Institute where he and his team are responsible for the provision of IT capabilities as well as effective data management platforms to support the broad range of science within the Institute.
Recent publications
-
A data science roadmap for open science organizations engaged in early-stage drug discovery.
Journal article
Edfeldt K. et al, (2024), Nat Commun, 15
-
Improving the representativeness of UK's national COVID-19 Infection Survey through spatio-temporal regression and post-stratification.
Journal article
Pouwels KB. et al, (2024), Nat Commun, 15
-
Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
Preprint
Ferla MP. et al, (2024)
-
Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population.
Journal article
Wei J. et al, (2024), Nat Commun, 15
-
Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases.
Journal article
Pagnamenta AT. et al, (2023), Genome Med, 15