Literature DB >> 18275175

Determination of complex reaction mechanisms. Analysis of chemical, biological and genetic networks.

John Ross.   

Abstract

We present several methods of determining, not guessing, complex chemical reaction mechanisms and their functions. One method is based on the theory of correlation functions of measured time series of concentrations of chemical species; another is on measurements of temporal responses of concentrations to various perturbations of arbitrary magnitude; a third deals with the analysis of oscillatory systems; a fourth is on the use of genetic algorithms to determine functions of chemical reaction networks. All methods are applicable to chemical, biochemical, and biological reaction systems and to genetic networks and systems biology. The methods depend on the design of appropriate experiments on the whole system and corresponding theories for interpretation that lead to information on the causal chemical connectivity of species, on reaction pathways, on reaction mechanisms, on control centers in the system, and on functions of the system. The first three methods require no assumption of a model or hypothesis, nor extensive calculations, unlike the interpretation of measurements made on a gene network at only one time.

Mesh:

Year:  2008        PMID: 18275175     DOI: 10.1021/jp711313e

Source DB:  PubMed          Journal:  J Phys Chem A        ISSN: 1089-5639            Impact factor:   2.781


  8 in total

1.  Multidimensional Measures of Response and Fluctuations in Stochastic Dynamical Systems.

Authors:  Maksym Kryvohuz; Shaul Mukamel
Journal:  Phys Rev A       Date:  2012-10-12       Impact factor: 3.140

2.  Characterizing multistationarity regimes in biochemical reaction networks.

Authors:  Irene Otero-Muras; Julio R Banga; Antonio A Alonso
Journal:  PLoS One       Date:  2012-07-03       Impact factor: 3.240

3.  On the reducible character of Haldane-Radić enzyme kinetics to conventional and logistic Michaelis-Menten models.

Authors:  Mihai V Putz
Journal:  Molecules       Date:  2011-04-13       Impact factor: 4.411

4.  Efficient, sparse biological network determination.

Authors:  Elias August; Antonis Papachristodoulou
Journal:  BMC Syst Biol       Date:  2009-02-23

5.  Signaling flux redistribution at toll-like receptor pathway junctions.

Authors:  Kumar Selvarajoo; Yasunari Takada; Jin Gohda; Mohamed Helmy; Shizuo Akira; Masaru Tomita; Masa Tsuchiya; Jun-Ichiro Inoue; Koichi Matsuo
Journal:  PLoS One       Date:  2008-10-17       Impact factor: 3.240

6.  Reverse engineering cellular networks with information theoretic methods.

Authors:  Alejandro F Villaverde; John Ross; Julio R Banga
Journal:  Cells       Date:  2013-05-10       Impact factor: 6.600

7.  A systems biology approach to suppress TNF-induced proinflammatory gene expressions.

Authors:  Kentaro Hayashi; Vincent Piras; Sho Tabata; Masaru Tomita; Kumar Selvarajoo
Journal:  Cell Commun Signal       Date:  2013-11-07       Impact factor: 5.712

8.  MIDER: network inference with mutual information distance and entropy reduction.

Authors:  Alejandro F Villaverde; John Ross; Federico Morán; Julio R Banga
Journal:  PLoS One       Date:  2014-05-07       Impact factor: 3.240

  8 in total

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