Literature DB >> 7579901

Comparative characterization of the fermentation pathway of Saccharomyces cerevisiae using biochemical systems theory and metabolic control analysis: model definition and nomenclature.

R Curto1, A Sorribas, M Cascante.   

Abstract

Mathematical tools that involve the determination of systemic responses to small changes in metabolites or enzymes have demonstrated their utility for analyzing metabolic pathways. The different methodologies based on these ideas allow for modeling and analyzing biochemical pathways focusing on the coordinate behavior of the whole system. However, one must become familiar with the difference in nomenclature and methodology to relate the models and results obtained by applying these techniques and to appreciate their potential for answering fundamental questions about biochemical systems. In the following three papers we show how this can be facilitated by comparing the nomenclature, methodology, and results of the two leading techniques in this area, metabolic control analysis and biochemical systems theory, using a model of the fermentation pathway in Saccharomyces cerevisiae as a reference system. In the present paper we review the nomenclature, technical concepts, and related experimental measurements while creating a practical dictionary for the reference system that makes the relatedness of the two approaches more apparent. In the second paper, subtitled Steady-State Analysis, we show that both approaches give the same picture for many systemic responses of the reference system. In the third paper of this series, subtitled Model Validation and Dynamic Behavior, we show that the quality of the model can be assessed by studying the sensitivity to changes in the system parameters. We hope to illustrate the usefulness of these tools in providing an interpretation of the experimental measurements in a specific metabolic pathway.

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Year:  1995        PMID: 7579901     DOI: 10.1016/0025-5564(94)00092-e

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  17 in total

Review 1.  Biological systems modeling and analysis: a biomolecular technique of the twenty-first century.

Authors:  Gautam Goel; I-Chun Chou; Eberhard O Voit
Journal:  J Biomol Tech       Date:  2006-09

2.  Validation and steady-state analysis of a power-law model of purine metabolism in man.

Authors:  R Curto; E O Voit; A Sorribas; M Cascante
Journal:  Biochem J       Date:  1997-06-15       Impact factor: 3.857

3.  Nonparametric dynamic modeling.

Authors:  Mojdeh Faraji; Eberhard O Voit
Journal:  Math Biosci       Date:  2016-08-30       Impact factor: 2.144

4.  In vivo NMR study of yeast fermentative metabolism in the presence of ferric irons.

Authors:  Maso Ricci; Silvia Martini; Claudia Bonechi; Daniela Braconi; Annalisa Santucci; Claudio Rossi
Journal:  J Biosci       Date:  2011-03       Impact factor: 1.826

5.  Analysis of abnormalities in purine metabolism leading to gout and to neurological dysfunctions in man.

Authors:  R Curto; E O Voit; M Cascante
Journal:  Biochem J       Date:  1998-02-01       Impact factor: 3.857

Review 6.  The best models of metabolism.

Authors:  Eberhard O Voit
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2017-05-19

Review 7.  Recent developments in parameter estimation and structure identification of biochemical and genomic systems.

Authors:  I-Chun Chou; Eberhard O Voit
Journal:  Math Biosci       Date:  2009-03-25       Impact factor: 2.144

8.  Stepwise inference of likely dynamic flux distributions from metabolic time series data.

Authors:  Mojdeh Faraji; Eberhard O Voit
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

9.  Multi-objective optimization of enzyme manipulations in metabolic networks considering resilience effects.

Authors:  Wu-Hsiung Wu; Feng-Sheng Wang; Maw-Shang Chang
Journal:  BMC Syst Biol       Date:  2011-09-19

10.  Integrating systemic and molecular levels to infer key drivers sustaining metabolic adaptations.

Authors:  Pedro de Atauri; Míriam Tarrado-Castellarnau; Josep Tarragó-Celada; Carles Foguet; Effrosyni Karakitsou; Josep Joan Centelles; Marta Cascante
Journal:  PLoS Comput Biol       Date:  2021-07-23       Impact factor: 4.475

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