Literature DB >> 11800577

Mathematical modeling of plant metabolic pathways.

John A Morgan1, David Rhodes.   

Abstract

The understanding of the control of metabolic flux in plants requires integrated mathematical formulations of gene and protein expression, enzyme kinetics, and developmental biology. Plants have a large number of metabolically active compartments, and non-steady-state conditions are frequently encountered. Consequently steady-state metabolic flux balance and isotopic flux balance modeling approaches have limited utility in probing plant metabolic systems. Transient isotopic flux analysis and kinetic modeling are powerful proven techniques for the quantification of metabolic fluxes in compartmentalized, dynamic metabolic systems. These tools are now widely used to address metabolic flux responses to environmental and genetic perturbations in plant metabolism. Continued developments in isotopic and kinetic modeling, quantifying metabolite exchange between compartments, and transcriptional and posttranscriptional regulatory mechanisms governing enzyme level and activity will enable simulation of large sections of plant metabolism under non-steady-state conditions. Metabolic control analysis will continue to make substantial contributions to the understanding of quantitative distribution of control of flux. From the synergy between mathematical models and experiments, creative methods for controlling the distribution of flux by genetic or environmental means will be discovered and rationally implemented.

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Year:  2002        PMID: 11800577     DOI: 10.1006/mben.2001.0211

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  15 in total

1.  Simulating plant metabolic pathways with enzyme-kinetic models.

Authors:  Kai Schallau; Björn H Junker
Journal:  Plant Physiol       Date:  2010-01-29       Impact factor: 8.340

2.  Arabidopsis reactome: a foundation knowledgebase for plant systems biology.

Authors:  Nicolas Tsesmetzis; Matthew Couchman; Janet Higgins; Alison Smith; John H Doonan; Georg J Seifert; Esther E Schmidt; Imre Vastrik; Ewan Birney; Guanming Wu; Peter D'Eustachio; Lincoln D Stein; Richard J Morris; Michael W Bevan; Sean V Walsh
Journal:  Plant Cell       Date:  2008-06-30       Impact factor: 11.277

Review 3.  Plant metabolic modeling: achieving new insight into metabolism and metabolic engineering.

Authors:  Kambiz Baghalian; Mohammad-Reza Hajirezaei; Falk Schreiber
Journal:  Plant Cell       Date:  2014-10-24       Impact factor: 11.277

4.  The metabolic response of heterotrophic Arabidopsis cells to oxidative stress.

Authors:  Charles J Baxter; Henning Redestig; Nicolas Schauer; Dirk Repsilber; Kiran R Patil; Jens Nielsen; Joachim Selbig; Junli Liu; Alisdair R Fernie; Lee J Sweetlove
Journal:  Plant Physiol       Date:  2006-11-22       Impact factor: 8.340

5.  Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning Model.

Authors:  Ophélie Lo-Thong-Viramoutou; Philippe Charton; Xavier F Cadet; Brigitte Grondin-Perez; Emma Saavedra; Cédric Damour; Frédéric Cadet
Journal:  Front Artif Intell       Date:  2022-06-10

6.  Flux balance analysis of barley seeds: a computational approach to study systemic properties of central metabolism.

Authors:  Eva Grafahrend-Belau; Falk Schreiber; Dirk Koschützki; Björn H Junker
Journal:  Plant Physiol       Date:  2008-11-05       Impact factor: 8.340

7.  Understanding in vivo benzenoid metabolism in petunia petal tissue.

Authors:  Jennifer Boatright; Florence Negre; Xinlu Chen; Christine M Kish; Barbara Wood; Greg Peel; Irina Orlova; David Gang; David Rhodes; Natalia Dudareva
Journal:  Plant Physiol       Date:  2004-07-30       Impact factor: 8.340

8.  Multiscale metabolic modeling: dynamic flux balance analysis on a whole-plant scale.

Authors:  Eva Grafahrend-Belau; Astrid Junker; André Eschenröder; Johannes Müller; Falk Schreiber; Björn H Junker
Journal:  Plant Physiol       Date:  2013-08-07       Impact factor: 8.340

9.  Granger causality in integrated GC-MS and LC-MS metabolomics data reveals the interface of primary and secondary metabolism.

Authors:  Hannes Doerfler; David Lyon; Thomas Nägele; Xiaoliang Sun; Lena Fragner; Franz Hadacek; Volker Egelhofer; Wolfram Weckwerth
Journal:  Metabolomics       Date:  2012-10-25       Impact factor: 4.290

10.  Molecular modeling of metabolism for allergen-free low linoleic acid peanuts.

Authors:  Godson O Osuji; Tassine K Brown; Sanique M South; Dwiesha Johnson; Shanique Hyllam
Journal:  Appl Biochem Biotechnol       Date:  2012-08-24       Impact factor: 2.926

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