Literature DB >> 20363732

Streamlining the construction of large-scale dynamic models using generic kinetic equations.

Delali A Adiamah1, Julia Handl, Jean-Marc Schwartz.   

Abstract

MOTIVATION: Studying biological systems, not just at an individual component level but at a system-wide level, gives us great potential to understand fundamental functions and essential biological properties. Despite considerable advances in the topological analysis of metabolic networks, inadequate knowledge of the enzyme kinetic rate laws and their associated parameter values still hampers large-scale kinetic modelling. Furthermore, the integration of gene expression and protein levels into kinetic models is not straightforward.
RESULTS: The focus of our research is on streamlining the construction of large-scale kinetic models. A novel software tool was developed, which enables the generation of generic rate equations for all reactions in a model. It encompasses an algorithm for estimating the concentration of proteins for a reaction to reach a particular steady state when kinetic parameters are unknown, and two robust methods for parameter estimation. It also allows for the seamless integration of gene expression or protein levels into a reaction and can generate equations for both transcription and translation. We applied this methodology to model the yeast glycolysis pathway; our results show that the behaviour of the system can be accurately described using generic kinetic equations.
AVAILABILITY AND IMPLEMENTATION: The software tool, together with its source code in Java, is available from our project web site at http://www.bioinf.manchester.ac.uk/schwartz/grape CONTACT: jean-marc.schwartz@manchester.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Year:  2010        PMID: 20363732     DOI: 10.1093/bioinformatics/btq136

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Systematic integration of experimental data and models in systems biology.

Authors:  Peter Li; Joseph O Dada; Daniel Jameson; Irena Spasic; Neil Swainston; Kathleen Carroll; Warwick Dunn; Farid Khan; Naglis Malys; Hanan L Messiha; Evangelos Simeonidis; Dieter Weichart; Catherine Winder; Jill Wishart; David S Broomhead; Carole A Goble; Simon J Gaskell; Douglas B Kell; Hans V Westerhoff; Pedro Mendes; Norman W Paton
Journal:  BMC Bioinformatics       Date:  2010-11-29       Impact factor: 3.169

2.  Construction of a genome-scale kinetic model of mycobacterium tuberculosis using generic rate equations.

Authors:  Delali A Adiamah; Jean-Marc Schwartz
Journal:  Metabolites       Date:  2012-07-03

3.  Bridging the gap between gene expression and metabolic phenotype via kinetic models.

Authors:  Francisco G Vital-Lopez; Anders Wallqvist; Jaques Reifman
Journal:  BMC Syst Biol       Date:  2013-07-22

4.  A novel process-based model of microbial growth: self-inhibition in Saccharomyces cerevisiae aerobic fed-batch cultures.

Authors:  Stefano Mazzoleni; Carmine Landi; Fabrizio Cartenì; Elisabetta de Alteriis; Francesco Giannino; Lucia Paciello; Palma Parascandola
Journal:  Microb Cell Fact       Date:  2015-07-30       Impact factor: 5.328

5.  Steady-state metabolite concentrations reflect a balance between maximizing enzyme efficiency and minimizing total metabolite load.

Authors:  Naama Tepper; Elad Noor; Daniel Amador-Noguez; Hulda S Haraldsdóttir; Ron Milo; Josh Rabinowitz; Wolfram Liebermeister; Tomer Shlomi
Journal:  PLoS One       Date:  2013-09-26       Impact factor: 3.240

  5 in total

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