Literature DB >> 10498775

Mathematical simulation and analysis of cellular metabolism and regulation.

I Goryanin1, T C Hodgman, E Selkov.   

Abstract

MOTIVATION: A better understanding of the biological phenomena observed in cells requires the creation and analysis of mathematical models of cellular metabolism and physiology. The formulation and study of such models must also be simplified as far as possible to cope with the increasing complexity demanded and exponential accumulation of the metabolic reconstructions computed from sequenced genomes.
RESULTS: A mathematical simulation workbench, DBsolve, has been developed to simplify the derivation and analysis of mathematical models. It combines: (i) derivation of large-scale mathematical models from metabolic reconstructions and other data sources; (ii) solving and parameter continuation of non-linear algebraic equations (NAEs), including metabolic control analysis; (iii) solving the non-linear stiff systems of ordinary differential equations (ODEs); (iv) bifurcation analysis of ODEs; (v) parameter fitting to experimental data or functional criteria based on constrained optimization. The workbench has been successfully used for dynamic metabolic modeling of some typical biochemical networks (Dolgacheva et al., Biochemistry (Moscow), 6, 1063-1068, 1996; Goldstein and Goryanin, Mol. Biol. (Moscow), 30, 976-983, 1996), including microbial glycolytic pathways, signal transduction pathways and receptor-ligand interactions. AVAILABILITY: DBsolve 5. 00 is freely available from http://websites.ntl.com/ approximately igor.goryanin. CONTACT: gzz78923@ggr.co.uk

Mesh:

Year:  1999        PMID: 10498775     DOI: 10.1093/bioinformatics/15.9.749

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


  22 in total

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Journal:  Plant Mol Biol       Date:  2002-01       Impact factor: 4.076

2.  A computer model of the gene network of the cholesterol biosynthesis regulation in the cell: analysis of the effect of mutations.

Authors:  A V Ratushnyi; V A Likhoshvai; E V Ignat'eva; Yu G Matushkin; I I Goryanin; N A Kolchanov
Journal:  Dokl Biochem Biophys       Date:  2003 Mar-Apr       Impact factor: 0.788

3.  BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes.

Authors:  Junhui Gao; Li Li; Xiaolin Wu; Dong-Qing Wei
Journal:  Protein Cell       Date:  2012-03-10       Impact factor: 14.870

4.  CADLIVE dynamic simulator: direct link of biochemical networks to dynamic models.

Authors:  Hiroyuki Kurata; Kouichi Masaki; Yoshiyuki Sumida; Rei Iwasaki
Journal:  Genome Res       Date:  2005-04       Impact factor: 9.043

5.  Mathematical modeling of mitochondrial adenine nucleotide translocase.

Authors:  Eugeniy Metelkin; Igor Goryanin; Oleg Demin
Journal:  Biophys J       Date:  2005-10-20       Impact factor: 4.033

6.  Modelling cellular processes with Python and Scipy.

Authors:  B G Olivier; J M Rohwer; J H S Hofmeyr
Journal:  Mol Biol Rep       Date:  2002       Impact factor: 2.316

Review 7.  Cell-signalling dynamics in time and space.

Authors:  Boris N Kholodenko
Journal:  Nat Rev Mol Cell Biol       Date:  2006-03       Impact factor: 94.444

8.  Kinetic model of mitochondrial Krebs cycle: unraveling the mechanism of salicylate hepatotoxic effects.

Authors:  Ekaterina Mogilevskaya; Oleg Demin; Igor Goryanin
Journal:  J Biol Phys       Date:  2006-10-26       Impact factor: 1.365

9.  [Yeast chaperone Hspl04 regulates gene expression on the posttranscriptional level].

Authors:  A A Rubel'; A F Saĭfitdinova; A G Lada; A A Nizhnikov; S G Inge-Vechtomov; A P Galkin
Journal:  Mol Biol (Mosk)       Date:  2008 Jan-Feb

10.  Simulation of a Petri net-based model of the terpenoid biosynthesis pathway.

Authors:  Aliah Hazmah Hawari; Zeti-Azura Mohamed-Hussein
Journal:  BMC Bioinformatics       Date:  2010-02-09       Impact factor: 3.169

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