Introduction

The Bioinformatics Group at University College London is headed by Professor David Jones, and was originally founded as the Joint Research Council funded Bioinformatics Unit within the Department of Computer Science at UCL. The Unit has now been fully integrated into the department as one of the 11 CS Research Groups. The group's main aim is to develop, and apply state-of-the-art computational techniques to tackle problems now arising in the life sciences, particularly those now appearing in the post-genomic era. A particular emphasis of the group is on applications of machine learning techniques to biological problems. The group's interdisciplinary research is closely linked with the Institute of Structural and Molecular Biology, though we also maintain and encourage links to other UCL departments and Centres. The Group also forms the research core of the Bloomsbury Centre for Bioinformatics, which is a joint Research Centre between UCL and Birkbeck College and which also provides bioinformatics training and support services to biomedical researchers at both universities. The Group occupies dedicated space within the Department of Computer Science, along with space shared with the Faculty of Life Sciences and makes full use of the available Departmental computing facilities, along with joint access to a 4000-core Linux Cluster housed within the Department. We also make extensive use of the 6000-core UCL Legion supercomputer. The Group also maintains some dedicated computing facilities of its own to allow maintenance of specialized biological databases and public access to the software and methods developed within the Group.

Group Research

Protein-DNA Interaction
Protein Structure Prediction
PSICOV Predicted Contact Map
Protein Stequence Analysis
  • Protein function prediction (ffpred)
  • Metsite: Metal binding residue prediction
  • HSPred : Protein-protein interaction characterisation
  • Amino acid substitution matrices
  • Hidden Markov Models (collaboration with N. Goldman, Cambridge, & J. Thorne, NCSU)
  • Amino acid co-evolution techniques (PSICOV)
Horseshoe
Genome Analysis
CATH
Protein Structure Classification
  • CATH (collaboration with C. Orengo, UCL Structural and Molecular Biology)
Transmembrane Protein Modelling
  • MEMSAT & MEMSATSVM
  • Folding In Lipid Membranes (FILM3)
  • MEMPACK
  • memembed
De novo Protein Design
  • Deep Learning and Generative Methods for protein design
Biological Applications of Data-mining and Machine Learning Techniques
  • Information extraction for biological research (BioRat)
Microarray Analysis
  • Data integration for microarray analysis
  • Data visualization
Systems Biology
  • Systems biology applied to stem cells
Web Services
  • Workflow Management Engines
  • Biographics