Literature DB >> 16303240

Generalized concept of minimal cut sets in biochemical networks.

Steffen Klamt1.   

Abstract

Recently, the concept of minimal cut sets has been introduced for studying structural fragility and identifying knock-out strategies in biochemical reaction networks. A minimal cut set (MCS) has been defined as a minimal set of reactions whose removal blocks the operation of a chosen objective reaction. In this report the theoretical framework of MCSs is refined and extended increasing the practical applicability significantly. An MCS is now defined as a minimal (irreducible) set of structural interventions (removal of network elements) repressing a certain functionality specified by a deletion task. A deletion task describes unambiguously the flux patterns (or the functionality) to be repressed. It is shown that the MCSs can be computed from the set of target modes, which comprises all elementary modes that exhibit the functionality to be attacked. Since a deletion task can be specified by several Boolean rules, MCSs can now be determined for a large variety of complex deletion problems and may be utilized for inhibiting very special flux patterns. It is additionally shown that the other way around is also possible: the elementary modes belonging to a certain functionality can be computed from the respective set of MCSs. Therefore, elementary modes and MCSs can be seen as dual representations of network functions and both can be converted into each other. Moreover, there exist a strong relationship to minimal hitting sets known from set theory: the MCSs are the minimal hitting sets of the collection of target modes and vice versa. Another generalization introduced herein is that MCSs need not to be restricted to the removal of reactions they may also contain network nodes. In the light of the extended framework of MCSs, applications for assessing, manipulating, and designing metabolic networks in silico are discussed.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16303240     DOI: 10.1016/j.biosystems.2005.04.009

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  29 in total

1.  Deep epistasis in human metabolism.

Authors:  Marcin Imielinski; Calin Belta
Journal:  Chaos       Date:  2010-06       Impact factor: 3.642

Review 2.  In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories.

Authors:  Paulo Maia; Miguel Rocha; Isabel Rocha
Journal:  Microbiol Mol Biol Rev       Date:  2015-11-25       Impact factor: 11.056

Review 3.  Boolean network modeling in systems pharmacology.

Authors:  Peter Bloomingdale; Van Anh Nguyen; Jin Niu; Donald E Mager
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-01-06       Impact factor: 2.745

4.  Computing smallest intervention strategies for multiple metabolic networks in a boolean model.

Authors:  Wei Lu; Takeyuki Tamura; Jiangning Song; Tatsuya Akutsu
Journal:  J Comput Biol       Date:  2015-02       Impact factor: 1.479

5.  Cutting the wires: modularization of cellular networks for experimental design.

Authors:  Moritz Lang; Sean Summers; Jörg Stelling
Journal:  Biophys J       Date:  2014-01-07       Impact factor: 4.033

6.  Finding MEMo: minimum sets of elementary flux modes.

Authors:  Annika Röhl; Alexander Bockmayr
Journal:  J Math Biol       Date:  2019-08-06       Impact factor: 2.259

7.  Automatic construction of metabolic models with enzyme constraints.

Authors:  Pavlos Stephanos Bekiaris; Steffen Klamt
Journal:  BMC Bioinformatics       Date:  2020-01-14       Impact factor: 3.169

8.  Quantification of metabolism in Saccharomyces cerevisiae under hyperosmotic conditions using elementary mode analysis.

Authors:  Jignesh H Parmar; Sharad Bhartiya; K V Venkatesh
Journal:  J Ind Microbiol Biotechnol       Date:  2012-02-22       Impact factor: 3.346

Review 9.  Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism.

Authors:  Cong T Trinh; Aaron Wlaschin; Friedrich Srienc
Journal:  Appl Microbiol Biotechnol       Date:  2008-11-15       Impact factor: 4.813

10.  Can the whole be less than the sum of its parts? Pathway analysis in genome-scale metabolic networks using elementary flux patterns.

Authors:  Christoph Kaleta; Luís Filipe de Figueiredo; Stefan Schuster
Journal:  Genome Res       Date:  2009-06-18       Impact factor: 9.043

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.