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SUMMARY:Standardisation of stoichiometric models: how and why - Swainston\
 , N (University of Manchester)
DTSTART:20141104T113000Z
DTEND:20141104T114500Z
UID:TALK55929@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Interest in constraint-based modelling of metabolism using sto
 ichiometric models has grown significantly over the last 10-15 years. Hund
 reds of curated models [1]\, and thousands of automatically generated mode
 ls [2] are now publicly available\, covering organisms in all three domain
 s.\n \nDespite attempts of standardising their representation\, using comm
 unity-developed formats such as the Systems Biology Markup Language\, SBML
  [3]\, many tasks surrounding model building and analysis are hampered by 
 a lack of interoperability between models.\n \nBased on the speaker's expe
 rience in co-leading two large international community efforts in the deve
 lopment of consensus models for yeast [4] and human [5]\, approaches to mo
 del standardisation will be discussed. Moreover\, the benefits of adopting
  a disciplined approach to model standardisation - automated model buildin
 g\, model checking\, and 'omics data integration - will be demonstrated.\n
  \nSuch reliance on automated techniques will be of particular relevance t
 o stoichiometric modelling of microbial communities\, where the complexity
  of such models is likely to far exceed that of even the largest existing 
 models of mammalian metabolism.\n \n[1] Optimizing genome-scale network re
 constructions. Monk J\, et al. Nat Biotechnol. 2014\, 32(5):447-52. [2] Pa
 th2Models: large-scale generation of computational models from biochemical
  pathway maps. Büchel F\, et al. BMC Syst Biol. 7:116. [3] The systems bi
 ology markup language (SBML): a medium for representation and exchange of 
 biochemical network models. Hucka M\, et al. Bioinformatics. 2003\, 19(4):
 524-31. [4] A consensus yeast metabolic network reconstruction obtained fr
 om a community approach to systems biology. Herrgård MJ\, et al. Nat Biot
 echnol. 2008\, 26(10):1155-60. [5] A community-driven global reconstructio
 n of human metabolism. Thiele I\, et al. Nat Biotechnol. 2013\, 31(5):419-
 25.
LOCATION:Seminar Room 1\, Newton Institute
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