Joint PhD Programme
in Structural, Computational, Cell and Chemical Biology
Funded by the BBSRC
Opportunities for discovery
This in-depth interdisciplinary programme is funded by the BBSRC and provides world-class PhD training in Structural, Computational and Chemical Biology. The programme is run jointly by the ISMB at the following departments:
BBSRC CASE studentship currently available
CASE (Collaborative Awards in Science and Engineering) PhD students are jointly supervised by academic and industrial partners. The successful applicants will begin their PhD studies in September 2010 with a tax-free stipend of over £1,200 per month and tuition fees paid in full at the home/EU rate.
Development of Highthroughput Methods for Adopting and Improving Microbial Metabolic Networks using Advanced Text Informatics
Principal PI: Dr Adrian Shepherd, Department of Biological Sciences, Birkbeck
Collaborating PI: Dr Adrian M Smith, Unilever R&D Colworth
Collaborating PI: Dr Irilenia Nobeli,
Department of Biological Sciences, Birkbeck
Collaborating PI: Dr Wendy Filsell, Unilever R&D Colworth
This project will involve developing an interactive tool for building, amending and analyzing models of microbial metabolic networks. The student will build on existing public resources (e.g. BioCyc, KEGG, IMG/HMP) to provide enhanced annotations, inference and hypothesis-testing capabilities. A key focus will be how to identify and incorporate relevant information extracted from the literature using advanced text-mining tools. The new tool developed under the project will be used to identify the consumer- and disease-relevance of specific microorganisms.
This CASE studentship is part of a collaboration between the Department of Biological Sciences at Birkbeck and Unilever. The student will be based at Birkbeck, but will also spend at least three months on a placement with Unilever Research & Development at the Colworth Science Park.
Rotation project 1: Natural language processing. The student will learn how to use a range of tools for extracting relationships between genes and proteins from full text articles. (A.Shepherd’s lab).
Rotation project 2: Metabolic network construction. The student will learn how to build annotated metabolic networks from genomic data using BioCyc and use such a network to draw inferences and test hypotheses. (Unilever).
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