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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. |
== News == === Metabolic Pathways Analysis 2017 - UPDATE === Bozeman, Montana USA, 24-28 July, 2017. '''Registration now open'''. See the [[http://www.chbe.montana.edu/biochemenglab/MPA2017.html|conference website]] and the the [[http://mpa.brookes.ac.uk|MPA website]] for more information. Abstract submission deadline: 21 April 2017. |
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| '''Registration and abstract submission''' now live! Speaker slots available for selected abstracts. | === International Study Group for Systems Biology === The last meeting took place 4-7 October 2016 in Jena, Germany. [[http://sysbio.brookes.ac.uk/|More details here]] and at the [[http://isgsb-2016.bioinf.uni-jena.de/|meeting website]]. Selected highlight will appear in Biochemical Society Transactions in August 2017. |
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| '''New paper online ahead of print:''' Maurice Cheung et al, A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions. The Plant Journal .[[http://onlinelibrary.wiley.com/doi/10.1111/tpj.12252/abstract|accepted manuscript]] | === Latest paper: === Ahmad Ahmad, Hassan B. Hartman , S. Krishnakumar, David A. Fell , Mark G. Poolman , Shireesh Srivastava. A Genome Scale Model of Geobacillus thermoglucosidasius (C56-YS93) reveals its biotechnological potential on rice straw hydrolysate. J. Biotech (in press, 2017) |
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| '''Previous paper: '''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]] ] ----- |
=== Previous papers: === Near-dead heat between: 1. Dipali Singh, Ross Carlson, David Fell and Mark Poolman. Modelling Metabolism of the Diatom ''Phaeodactylum tricornutum''. Biochem. Soc. Trans. 43, 1182- (2015) [[http://www.biochemsoctrans.org/content/43/6/1182|PDF]] doi:10.1042/BST20150152 1. Huili Yuan, C. Y. Maurice Cheung, Mark G. Poolman, Peter A.J. Hilbers and Natal A.W. van Riel. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism. The Plant Journal, accepted m/s DOI: 10.1111/tpj.13075 [[http://onlinelibrary.wiley.com/doi/10.1111/tpj.13075/abstract|abstract]] |
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| * [[http://sysbio.brookes.ac.uk|The website of the International Study Group for Systems Biology]] |
* [[http://sysbio.brookes.ac.uk|The website of the International Study Group for Systems Biology]] |
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| * [[http://mpa.brookes.ac.uk|The website for the Metabolic Pathways Analysis series of meetings]] | |
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| * [[http://mpa.brookes.ac.uk|The website for the Metabolic Pathways Analysis series of meetings]] |
* [[http://mitoscop.brookes.ac.uk|The website for the BBSRC-ANR project MitoScoP]] |
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* [[http://mitoscop.brookes.ac.uk|The website for the BBSRC-ANR project MitoScoP]] * [[http://frim.brookes.ac.uk|The website for the EraSysBio+ project Fruit Integrative Modelling]] |
* [[http://frim.brookes.ac.uk|The website for the EraSysBio+ project Fruit Integrative Modelling]] |
News
Metabolic Pathways Analysis 2017 - UPDATE
Bozeman, Montana USA, 24-28 July, 2017. Registration now open. See the conference website and the the MPA website for more information. Abstract submission deadline: 21 April 2017.
International Study Group for Systems Biology
The last meeting took place 4-7 October 2016 in Jena, Germany. More details here and at the meeting website. Selected highlight will appear in Biochemical Society Transactions in August 2017.
Latest paper:
Ahmad Ahmad, Hassan B. Hartman , S. Krishnakumar, David A. Fell , Mark G. Poolman , Shireesh Srivastava. A Genome Scale Model of Geobacillus thermoglucosidasius (C56-YS93) reveals its biotechnological potential on rice straw hydrolysate. J. Biotech (in press, 2017)
Previous papers:
Near-dead heat between:
Dipali Singh, Ross Carlson, David Fell and Mark Poolman. Modelling Metabolism of the Diatom Phaeodactylum tricornutum. Biochem. Soc. Trans. 43, 1182- (2015) PDF doi:10.1042/BST20150152
Huili Yuan, C. Y. Maurice Cheung, Mark G. Poolman, Peter A.J. Hilbers and Natal A.W. van Riel. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism. The Plant Journal, accepted m/s DOI: 10.1111/tpj.13075 abstract
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: