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| === Meeting news === '''Metabolic Pathway Analysis 2013''' will be held in Oxford, 16-20 September. See its [[http://www.accliphot.eu/mpa-2013/|website]] for details. |
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| '''Registration and abstract submission''' now live! Speaker slots available for selected abstracts. | '''Metabolic Pathways Analysis 2015.''' The dates (8-12 June 2014) and the location near Braga, Portugal, have been fixed. More information and links are on our [[Meetings]] page. |
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| '''New paper out now: '''Mark G. Poolman, Sudip Kundu, Rahul Shaw and David A Fell. Responses to Light Intensity in a Genome–Scale Model of Rice Metabolism. ''Plant Physiology'', 162, 1060-1072, 2013, [[./Publications/articles|PDF]] available. [ [[http://dx.doi.org/10.1104/pp.113.216762|DOI: 10.1104/pp.113.216762]] ] ----- |
'''Latest paper:''' Mark G. Poolman, Sudip Kundu, Rahul Shaw and David A. Fell. Metabolic Trade-offs between Biomass Synthesis and Photosynthate Export at Different Light Intensities in a Genome–Scale Metabolic Model of Rice. Frontiers in Plant Science, 00656 (2014) [[http://journal.frontiersin.org/Journal/10.3389/fpls.2014.00656/abstract|Provisional PDF]] '''Previous paper:''' Hassan B. Hartman, David A. Fell, Sergio Rossell, Peter Ruhdal Jensen, Martin J. Woodward, Lotte Thorndahl, Lotte Jelsbak, John Elmerdahl Olsen, Anu Raghunathan, Simon Daefler,and Mark G. Poolman. Identification of potential drug targets in ''Salmonella enterica'' sv. Typhimurium using metabolic modelling and experimental validation. Microbiology 160:1252-1266 (2014) [[http://dx.doi.org/10.1099/mic.0.076091-0|DOI:10.1099/mic.0.076091-0]] This article was the Editor's Choice article for the June issue of Microbiology. |
News
Metabolic Pathways Analysis 2015. The dates (8-12 June 2014) and the location near Braga, Portugal, have been fixed. More information and links are on our Meetings page.
Latest paper: Mark G. Poolman, Sudip Kundu, Rahul Shaw and David A. Fell. Metabolic Trade-offs between Biomass Synthesis and Photosynthate Export at Different Light Intensities in a Genome–Scale Metabolic Model of Rice. Frontiers in Plant Science, 00656 (2014) Provisional PDF
Previous paper: Hassan B. Hartman, David A. Fell, Sergio Rossell, Peter Ruhdal Jensen, Martin J. Woodward, Lotte Thorndahl, Lotte Jelsbak, John Elmerdahl Olsen, Anu Raghunathan, Simon Daefler,and Mark G. Poolman. Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation. Microbiology 160:1252-1266 (2014) DOI:10.1099/mic.0.076091-0 This article was the Editor's Choice article for the June issue of Microbiology.
Background
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.
Related Sites
We also host the following web sites related to our research: