Literature DB >> 15300679

Modelling the dynamics of the yeast pheromone pathway.

Bente Kofahl1, Edda Klipp.   

Abstract

We present a mathematical model of the dynamics of the pheromone pathways in haploid yeast cells of mating type MATa after stimulation with pheromone alpha-factor. The model consists of a set of differential equations and describes the dynamics of signal transduction from the receptor via several steps, including a G protein and a scaffold MAP kinase cascade, up to changes in the gene expression after pheromone stimulation in terms of biochemical changes (complex formations, phosphorylations, etc.). The parameters entering the models have been taken from the literature or adapted to observed time courses or behaviour. Using this model we can follow the time course of the various complex formation processes and of the phosphorylation states of the proteins involved. Furthermore, we can explain the phenotype of more than a dozen well-characterized mutants and also the graded response of yeast cells to varying concentrations of the stimulating pheromone.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15300679     DOI: 10.1002/yea.1122

Source DB:  PubMed          Journal:  Yeast        ISSN: 0749-503X            Impact factor:   3.239


  43 in total

Review 1.  Integration of metabolic reactions and gene regulation.

Authors:  Chen-Hsiang Yeang
Journal:  Mol Biotechnol       Date:  2011-01       Impact factor: 2.695

2.  Kinetic diversity in G-protein-coupled receptor signalling.

Authors:  Vladimir L Katanaev; Matey Chornomorets
Journal:  Biochem J       Date:  2007-01-15       Impact factor: 3.857

3.  Identification of the molecular mechanisms for cell-fate selection in budding yeast through mathematical modeling.

Authors:  Yongkai Li; Ming Yi; Xiufen Zou
Journal:  Biophys J       Date:  2013-05-21       Impact factor: 4.033

4.  Do cells make decisions based on uncertainty in their biochemical networks?

Authors:  Pavel Kraikivski
Journal:  Biophys J       Date:  2013-05-21       Impact factor: 4.033

5.  A physiologically required G protein-coupled receptor (GPCR)-regulator of G protein signaling (RGS) interaction that compartmentalizes RGS activity.

Authors:  Wayne Croft; Claire Hill; Eilish McCann; Michael Bond; Manuel Esparza-Franco; Jeannette Bennett; David Rand; John Davey; Graham Ladds
Journal:  J Biol Chem       Date:  2013-07-30       Impact factor: 5.157

6.  Model aggregation: a building-block approach to creating large macromolecular regulatory networks.

Authors:  Ranjit Randhawa; Clifford A Shaffer; John J Tyson
Journal:  Bioinformatics       Date:  2009-10-29       Impact factor: 6.937

7.  Quantitative measurement of protein relocalization in live cells.

Authors:  Alan Bush; Alejandro Colman-Lerner
Journal:  Biophys J       Date:  2013-02-05       Impact factor: 4.033

8.  Statistical Analysis of Discrete Dynamical System Models for Biological Networks.

Authors:  Zhengyu Ouyang; Mingzhou Joe Song
Journal:  Proc Int Joint Conf Bioinforma Syst Biol Intell Comput       Date:  2009-09-25

9.  Optimal in silico target gene deletion through nonlinear programming for genetic engineering.

Authors:  Chung-Chien Hong; Mingzhou Song
Journal:  PLoS One       Date:  2010-02-24       Impact factor: 3.240

10.  Deterministic mathematical models of the cAMP pathway in Saccharomyces cerevisiae.

Authors:  Thomas Williamson; Jean-Marc Schwartz; Douglas B Kell; Lubomira Stateva
Journal:  BMC Syst Biol       Date:  2009-07-16
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.