Literature DB >> 23537990

Comparing methods for metabolic network analysis and an application to metabolic engineering.

Namrata Tomar1, Rajat K De.   

Abstract

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.
Copyright © 2013 Elsevier B.V. All rights reserved.

Mesh:

Substances:

Year:  2013        PMID: 23537990     DOI: 10.1016/j.gene.2013.03.017

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  16 in total

Review 1.  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

Review 2.  Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies.

Authors:  Predrag Horvat; Martin Koller; Gerhart Braunegg
Journal:  World J Microbiol Biotechnol       Date:  2015-06-12       Impact factor: 3.312

3.  Agent-based spatiotemporal simulation of biomolecular systems within the open source MASON framework.

Authors:  Gael Pérez-Rodríguez; Martín Pérez-Pérez; Daniel Glez-Peña; Florentino Fdez-Riverola; Nuno F Azevedo; Anália Lourenço
Journal:  Biomed Res Int       Date:  2015-03-22       Impact factor: 3.411

4.  FastPros: screening of reaction knockout strategies for metabolic engineering.

Authors:  Satoshi Ohno; Hiroshi Shimizu; Chikara Furusawa
Journal:  Bioinformatics       Date:  2013-11-19       Impact factor: 6.937

Review 5.  Predictive sulfur metabolism - a field in flux.

Authors:  Alexander Calderwood; Richard J Morris; Stanislav Kopriva
Journal:  Front Plant Sci       Date:  2014-11-18       Impact factor: 5.753

6.  Enhancing microbial metabolite and enzyme production: current strategies and challenges.

Authors:  Koichi Tamano
Journal:  Front Microbiol       Date:  2014-12-18       Impact factor: 5.640

7.  Metabolomics analysis: Finding out metabolic building blocks.

Authors:  Ricardo Alberich; José A Castro; Mercè Llabrés; Pere Palmer-Rodríguez
Journal:  PLoS One       Date:  2017-05-11       Impact factor: 3.240

8.  A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database.

Authors:  Daniel S Weaver; Ingrid M Keseler; Amanda Mackie; Ian T Paulsen; Peter D Karp
Journal:  BMC Syst Biol       Date:  2014-06-30

9.  Double and multiple knockout simulations for genome-scale metabolic network reconstructions.

Authors:  Yaron Ab Goldstein; Alexander Bockmayr
Journal:  Algorithms Mol Biol       Date:  2015-01-09       Impact factor: 1.405

10.  CompNet: a GUI based tool for comparison of multiple biological interaction networks.

Authors:  Bhusan K Kuntal; Anirban Dutta; Sharmila S Mande
Journal:  BMC Bioinformatics       Date:  2016-04-26       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.