Theoretical Systems Biology

I am a BBSRC Case Phd student (co-sponsored by Unilever), co-supervised by Prof. Michael Stumpf and Wendy Filsell at Unilever. My undergraduate degree was in Computer Science from the University of Nottingham and I obtained a distinction in my Masters degree in Bioinformatics and Theoretical Systems Biology from Imperial College London.

I am investigating how text mining and natural language processing techniques can be applied to the biological literature to help with problems in Systems Biology. The literature contains a large amount of unstructured knowledge about biological systems.

• distinguishing the species of named entities in biological/biomedical text
• relation extraction using a variety of machine learning approaches
• performing functional annotation of genes using the literature
• automatically generating mathematical models of biological systems using the literature

I help organise the London Biogeeks meetings at Imperial College and organised the Elements of Statistical Learning book group.

Disambiguating the Species of Named Entities using random walks over a mixture of adjacency matrices.

Integration of copy number, gene expression and pathways to investigate the ependymoma genome – UKAffy 2008

3rd place – Outstanding Second year PhD Research Poster – 2010