Literature DB >> 23219184

From measurement to implementation of metabolic fluxes.

Lars M Blank1, Birgitta E Ebert.   

Abstract

The intracellular reaction rates (fluxes) are the ultimate outcome of the activities of the complete inventory (from DNA to metabolite) and in their sum determine the cellular phenotype. The genotype-phenotype relationship is fundamental in such different fields as cancer research and biotechnology. Here, we summarize the developments in determining metabolic fluxes, inferring major pathways from the DNA-sequence, estimating optimal flux distributions, and how these flux distributions can be achieved in vivo. The technical advances to intervene with the many levels of the cellular architecture allow the implementation of new strategies in for example Metabolic Engineering.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2012        PMID: 23219184     DOI: 10.1016/j.copbio.2012.10.019

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


  5 in total

1.  Quantifying Dynamic Regulation in Metabolic Pathways with Nonparametric Flux Inference.

Authors:  Fei He; Michael P H Stumpf
Journal:  Biophys J       Date:  2019-04-19       Impact factor: 4.033

2.  Plastic waste as a novel substrate for industrial biotechnology.

Authors:  Nick Wierckx; M Auxiliadora Prieto; Pablo Pomposiello; Victor de Lorenzo; Kevin O'Connor; Lars M Blank
Journal:  Microb Biotechnol       Date:  2015-08-25       Impact factor: 5.813

Review 3.  Forward Individualized Medicine from Personal Genomes to Interactomes.

Authors:  Xiang Zhang; Jan A Kuivenhoven; Albert K Groen
Journal:  Front Physiol       Date:  2015-12-09       Impact factor: 4.566

4.  Let's talk about flux or the importance of (intracellular) reaction rates.

Authors:  Lars M Blank
Journal:  Microb Biotechnol       Date:  2016-11-11       Impact factor: 5.813

5.  Derivative processes for modelling metabolic fluxes.

Authors:  Justina Zurauskienė; Paul Kirk; Thomas Thorne; John Pinney; Michael Stumpf
Journal:  Bioinformatics       Date:  2014-02-26       Impact factor: 6.937

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.