PhD studentship available for September 2014: The group has a BBSRC iCASE studentship on Modelling acetogen metabolism. See the project page for details of the research and important eligibility information.
RICEFUEL: The group is following up its existing interests in bioenergy research by participating in the UK-India project RICEFUEL coordinated by Nigel Minton at the University of Nottingham. See the BBSRC News for a report of the official announcement. Our project page is under construction at RiceFuel.
BBSRC Network in Industrial Biotechnology and Bioenergy (NIBB): David Fell will also be assisting Nigel Minton in running the C1NET: Chemicals from C1 gas NIBB. See the BBSRC and Oxford Brookes University announcements.
Latest paper: Uldis Kalnenieks, Agris Pentjuss, Reinis Rutkis, Egils Stalidzans and David A. Fell. Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies. Front. Microbiol. 5:42. doi: 10.3389/fmicb.2014.00042 (Open access)
Previous paper: Reinis Rutkis, Uldis Kalnenieks,Egils Stalidzans and David A. Fell. Kinetic modeling of Zymomonas mobilis Entner-Doudoroff pathway: insights into control and functionality. Microbiology (2013) DOI 10.1099/mic.0.071340-0 PDF
Our group began nearly thirty years ago with initial interests in computer simulation of metabolism and the theoretical analysis of metabolic control and regulation. Whilst these still remain areas of interest, we have since developed interests in modelling signal transduction, in various different approaches to network analysis of metabolism, and in reconstructing metabolic networks from genomic data. In the course of this research, we have addressed problems in microbial, plant and mammalian metabolism, often in conjunction with collaborators who have contributed experimental results.
Our current work centres on modelling the networks of reactions in cells, with particular emphasis on metabolism. It forms part of the emerging field of Systems Biology, in that we are concerned with understanding how biological function arises from the interactions between many components, and with building predictive models. We have to develop and apply suitable theoretical tools, including metabolic control analysis, computer simulation and other forms of algebraic and numerical analysis. In addition, we are investigating how to decipher the metabolic information contained in genome sequences. We are involved in projects on microbial, plant and animal metabolism, each in collaboration with an experimental team.
Potential applications of our work include the design of changes in cellular metabolism to improve the output of product such as antibiotics, detecting vulnerable sites in cellular networks that could be targets for drugs to control disease-causing organisms, and improved understanding of how organisms manage to adjust their metabolism in response to environmental changes and other signals.
We also host the following web sites related to our research: