I am a reader in BioHealth Informatics in the Bio and Health Informatics Group at the University of Manchester. I have a B.Sc. in biochemistry; an M.Sc. in biological Computation; and a D.Phil. in Computer Science: A blend of Biology and Computer Science, that I use within my main research area of Bioinformatics. I have close collaborations with the Information Management Group for both e-Science and description logics. I also have close affiliation with the Bioinformatics Groups from the Faculty of Life Sciences.
My main areas of research interest within these domains are the development and use of ontologies to describe biology to make knowledge about molecular biology computationally useful. I am particularly interested in the communal building of ontologies -- enabling domain experts to use the power of formal, expressive languages, such as the Web Ontology Language (OWL). This interest extends back from this formal part of the process of ontology building back to the initial stages of the process where I have an interest in rapid development of vocabularies and ontologies from text. I also have an interest in e-Science with the use of the taverna workbench from the myGrid project to industrialise the bioinformatics analysis of data. Ontologies and semantic description of content through ontologies also plays a part in this e-Science research.
I have another, completely different, research area in accessibility of information on computers by people with a visual disability. In this work my main interests are in how to make complex information tyeps as usable as possible by visually disabled, mainly blind, people. The high visual complexity of many of today's Web pages makes the Web one of these information types, but my interest expands to presentations of mathematics, chemical formulae and information in tables.
Contact DetailsRoom 2.91,
School of Computer Science,
The University of Manchester,
Voice: +44 (0) 161 275 6251 Email: email@example.com
I use this section to recent papers and publication highlights
This paper on modelling biological knowledge in OWL talks about what can and cannot be represented in OWL.
This paper describes the use of an an ontolog written in OWL to classify types of protein. The technique has been used to discover new proteins, especially in a recent survey of the phosphatases in three parasite genomes.
this paper on semantic similarity has been widely cited and used across the bioinformatics community.
School of Computer Science