Literature DB >> 21353523

Mechanistic pathway modeling for industrial biotechnology: challenging but worthwhile.

Wolfgang Wiechert1, Stephan Noack.   

Abstract

Mechanistic (also called kinetic) models quantitatively describe dynamic and steady states of biochemical pathways. They are based on network structure (stoichiometry), regulatory information (enzyme inhibitors and activators) and the corresponding reaction kinetics. Although this approach to understand and predict the behavior of biochemical networks has now been in use for almost half a century, its experimental foundation has dramatically changed in the data-rich age of systems biology. Large mechanistic models, ranging up to the genome scale, are now being built and lots of data are available to validate and test them. From the broad scope of possible modeling applications, this survey focuses on the recent developments and central problems of metabolic network modeling in the field of bioprocess development for industrial biotechnology.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21353523     DOI: 10.1016/j.copbio.2011.01.001

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  9 in total

1.  Error propagation analysis for quantitative intracellular metabolomics.

Authors:  Jana Tillack; Nicole Paczia; Katharina Nöh; Wolfgang Wiechert; Stephan Noack
Journal:  Metabolites       Date:  2012-11-21

Review 2.  Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

Authors:  Michalis Koutinas; Alexandros Kiparissides; Efstratios N Pistikopoulos; Athanasios Mantalaris
Journal:  Comput Struct Biotechnol J       Date:  2013-03-10       Impact factor: 7.271

3.  Fast "Feast/Famine" Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae.

Authors:  Camilo A Suarez-Mendez; Andre Sousa; Joseph J Heijnen; Aljoscha Wahl
Journal:  Metabolites       Date:  2014-05-15

4.  Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems.

Authors:  Attila Gábor; Alejandro F Villaverde; Julio R Banga
Journal:  BMC Syst Biol       Date:  2017-05-05

5.  Multiscale dynamic modeling and simulation of a biorefinery.

Authors:  Tobias Ploch; Xiao Zhao; Jonathan Hüser; Eric von Lieres; Ralf Hannemann-Tamás; Uwe Naumann; Wolfgang Wiechert; Alexander Mitsos; Stephan Noack
Journal:  Biotechnol Bioeng       Date:  2019-07-21       Impact factor: 4.530

6.  A simple method for identifying parameter correlations in partially observed linear dynamic models.

Authors:  Pu Li; Quoc Dong Vu
Journal:  BMC Syst Biol       Date:  2015-12-14

Review 7.  Adaptive laboratory evolution -- principles and applications for biotechnology.

Authors:  Martin Dragosits; Diethard Mattanovich
Journal:  Microb Cell Fact       Date:  2013-07-01       Impact factor: 5.328

Review 8.  Transcription factor-based biosensors in biotechnology: current state and future prospects.

Authors:  Regina Mahr; Julia Frunzke
Journal:  Appl Microbiol Biotechnol       Date:  2015-10-31       Impact factor: 4.813

Review 9.  A Review of Dynamic Modeling Approaches and Their Application in Computational Strain Optimization for Metabolic Engineering.

Authors:  Osvaldo D Kim; Miguel Rocha; Paulo Maia
Journal:  Front Microbiol       Date:  2018-07-31       Impact factor: 5.640

  9 in total

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