| PI | | Research Description and Weblinks |
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| | Dr Kevin Bryson  Dept. of Computer Science, UCL  | | Now a lecturer in Bioinformatics and Systems Biology, Dr. Bryson has previously worked on a project titled 'Functional Genomics of Pluripotent Stem Cells and their Progeny' which involves the investigation of stem cells with an emphasis on their clinical uses, for instance, stem cell therapy. Microarray technology was used to determine gene profiles for stem cells and key regulators in their differentiation. Dr Bryson's research interests cover many different aspects of bioinformatics and computational biology, including: genome analysis and annotation; protein structure prediction; transcriptomics; systems biology; stem cells; data modelling (W3 standards, MOF, UML); distributed systems (Web applications, Web services, multi-agent systems)Dr. Bryson is a member of the 'Functional Genomics of Pluripotent Stem Cells and their Progeny' project. | | | | | | Prof. Anthony Finkelstein  Dept. of Computer Science, UCL | | The immense scale and complexity of systems biology challenge should be clear, even if we assume the data were in place and the science wholly understood, which, of course, it is not. We are looking at computational models that are larger and much more complex than anything we have built hitherto. The data infrastructure required must handle volumes greater, and structures more elaborate, than anything we have tackled before. This prior to taking into account the implications of personalisation, let alone the considerations associated with applying this in medical settings. These add up, in short to the largest computational engineering challenge ever faced. For this we need proper engineering foundations - this is where my research interests are. What are these engineering foundations? Well first we need to specify requirements. In this context that means first we need to indicate precisely what 'properties' the models must be capable of reasoning about. We need an understanding of how the models are to be used. We also need some real sense of the 'volumetrics': just how large a problem we are facing, we know it is big, but we have no empirically well founded sense of the dimensions and scale. Next we need an architecture - a structural and conceptual framework to build on. Such an architecture must incorporate some principles of modularity and definitions of key interfaces. No large engineering project can be undertaken without the ability to reduce complexity by dividing a system into parts. Given that the models we are interested in are multi-dimensional, the types of modularity required are necessarily going to be sophisticated. In particular we need to arrive at some notion of a 'component' that has engineering utility but also corresponds to (or can be mapped onto) biological reality. We need a plan. We need to marshall our resources. We cannot simply work in an uncoordinated manner at different levels on different phenomena and believe that everything will just 'come together'. Finally, we need a framework of constructional tools. These tools would include languages, frameworks for data management, collaborative environments and, critically, an infrastructure for recording progress and managing the versioning and configuration of the model and its component parts. | | | | |  | | | Dr Mike Hubank
Institute of Child Health, UCL  | | Dr Mike Hubank directs the UCL Genomics lab, now integrated into the Centre for Translational Omics. Main Interests/Achievements: Genomic medicine is fundamental to many exciting research projects at UCL, including: Hypertrophic Cardiomyopathy; Antigen Receptor Repertoire; Pathogen Diagnostics Cancer Diagnostics and Monitoring; Gene Discovery; Gene and Cell Therapy. | | | | | | | | | | Prof. David Jones
Bioinformatics Group, Dept. of Computer Science, UCL  | | Prof. Jones's principal research interests are in protein structure prediction and analysis and simulations of protein folding. Under direction from Prof. Jones, the Bioinformatics Group's main aim is to develop and apply state-of-the-art mathematical and computer science techniques to problems now arising in the life sciences. David Jones is actively involved in the e-Protein project which uses GRID technology to provide a structure-based annotation of the proteins in the major genomes (i.e. the proteomes). The annotation primarily employs sophisticated homology and fold recognition methods to assign protein structures to the proteomes and generate 3D models. Enhanced functional annotation exploits the structural information. This project is a collaboration with Imperial College and the European Bioinformatics Institute.In collaboration with Bernard Buxton and David Corney, David Jones has also helped develop BioRat, a novel search engine which can be used to identify publications. The software allows you to find and download biological research papers via a PubMed-type search. | | | | | | Dr Andrew Martin
BSM group, Dept. of Biochemistry, UCL  | | Dr. Martin is best known for his work on analysis and modelling of antibodies and analysis of the effects of mutations on protein structure and function. His group is analysing antibody sequence and structure with a view to understanding how the immune system tailors binding to a given antigen and how antibodies can be humanised or sythesised. Initial studies of the effects of mutations concentrated on the tumour suppressor protein p53, but now looks at all proteins for which mutation data are available. Protocols for the analysis of the structural and functional consequences of single amino acid mutations are being enhanced with a view to using them predictively. Other work in the group has looked at improving sequence alignment for protein modelling and creating automated pipelines for protein sequence annotation. | | | | | | Dr Irilenia Nobeli
Department of Biological Sciences
Birkbeck, University of London | | The group is interested in the development and application of bioinformatics and chemoinformatics methods to analyse and compare small molecules, understand and predict molecular recognition (both protein-protein and protein-ligand interactions), and predict protein function with emphasis on catalytic and interaction promiscuity. More recently we are also interested in the reconstruction of metabolic pathways and the discovery of regulatory RNAs in bacterial and eukaryotic genomes. | | | | | | Prof. Christine Orengo
BSM group, Dept. of Biochemistry, UCL  | | Prof. Orengo's research chiefly concerns the development of algorithms for the classification of domain and protein families, the main products of this research being the CATH and Gene3D databases. Her group is also involved in designing methods to identify sequence or structural features associated with specific functional properties, with the ultimate goal of being able to predict the possible function of any gene sequence assigned to one of the protein families in the database.
Databases: CATH, DHS, Gene3D
URL: Homepage | | | | | | Dr Karen Page
Dept. of Mathematics, UCL  | | Dr. Page's research interests include mathematical modelling of cancer (including tumorigenesis and cancer dormancy), embryonic development and pattern formation, and cellular signalling networks, evolutionary dynamics and game theory. | | | | | | Prof. Stephen Perkins
BSM group, Dept. of Biochemistry, UCL  | | Prof Perkins is best known for his protein solution structural studies of antibodies and complement, including the atomistic modelling of their X-ray and neutron small angle scattering (SAS) curves using advanced protein simulation technologies, side-by-side with the database analysis of the effects of mutations on the coagulation and complement of proteins. He is the lead PI for the CCP-SAS computational project funded by the EPSRC and the NSF (see http://www.ccpsas.org/). He has developed websites that bring together phenotypic and structural information on four complement proteins, namely factor H, complement C3, membrane cofactor protein and factor I (associated with age-related macular degeneration and renal failure) and four coagulation proteins, namely factors VII, VIII, IX and XI (associated with bleeding disorders). | | | | | | Prof. Alex Poulovassilis
School of Computer Science and Information Systems, Birkbeck College | | Alex Poulovassilis's research centres on the areas of information
management and data integration in distributed environments. She is
interested in techniques for querying, integrating, visualiasing and
personalising information, particularly as arising in learning
environments and scientific data management.Tools: AutoMed (model based data integration package)
URL: Homepage | | | | | | Dr Adrian Shepherd
Department of Biological Sciences
Birkbeck, University of London  | | Dr Shepherd's research is in two distinct areas: immunoinformatics and
biomedical text mining. He is currently working with the WHO Influenza
Centre to analyze the antigenicity of epidemic influenza, and with
clinicians at UCL and Barts on treatments for haemophilia. He is also
collaborating with Unilever to develop text mining methods that support
the construction and curation of microbial metabolic pathways.Collaborators:
Dr John McCauley (Director of the WHO Influenza Centre, NIMR)
Dr Keith Gomez (Consultant in Haemostasis, Royal Free/UCL Medical School)
Dr Dan Hart (Consultant in Haemostasis, Barts/Queen Mary)
Dr Amit Nathwani (Reader in Haemostasis, UCL Cancer Institute)
Adrian M Smith (Unilever) | | | | | | Dr Maya Topf 
Department of Biological Sciences
Birkbeck, University of London | | Dr. Topf's research is focused on the development of computational methods that combine experimental data with bioinformatics and modeling techniques to characterise the structure of proteins and their assemblies. The structural models are further analysed to understand the dynamics and the effect of mutations on function. Her group is particularly interested in applying these methods using data from cryo electron microscopy and mass spectrometry. In collaboration with experimentalists, systems the group currently studies include the Herpes Simplex Virus, the molecular chaperonin GroEL, bacterial secretion systems, glycine transporters and ligand-gated ion channels. | | | | | | Prof. Bonnie Wallace
Department of Biological Sciences
Birkbeck, University of London | | Prof. Wallace's research incorporates Bioinformatics studies with experimental research in Structural Biology and Biophysics. Her research falls in two general areas: Studies on the structure and function of Voltage-Gated Sodium Channels, which includes molecular modelling and ligand docking studies as the basis for rational drug design, and methods development for Circular Dichroism spectroscopy, which includes the development of the popular Dichroweb secondary structure analysis website, the creation of the CDtoools software for spectral processing, analysis and archiving, and the development of the Protein Circular Dichroism Data Bank (PCDDB), a deposition and searchable archives of macromolecular circular dichroism spectra and metadata. | | | | | | Dr Mark Williams
Department of Biological Sciences
Birkbeck, University of London | | Dr Williams' research is concerned with understanding the structural and physical principles of biomolecular complex formation and how those principles control the behaviour of heterogeneous populations of complexes in functional biological systems. A wide variety of computational approaches are used by the group to complement and interpret experimental data. The group are engaged in the development of databases and structural analysis tools to enable investigation of correlations between structure and the thermodynamics of molecular interactions, in trying to improve the quality of tools for protein structure determination, and in the creation and application of software for the stochastic simulation of biological systems from the atomic to the cellular level. | | | | | | Dr Ziheng Yang
Department of Genetics, Evolution and Environment, UCL | | Professor Ziheng Yang's research is in the fields of molecular evolution, molecular systematics, population genetics, and computational biology. Statistical methods and computational algorithms are developed to infer species phylogenies and to study the mechanisms of molecular sequence evolution. Models of DNA and protein sequence evolution are implemented using likelihood and Bayesian methods. In addition to modelling, genomic data sets are analysed to detect adaptive molecular evolution and to estimate species divergence times. |
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