Steady-state expression of self-regulated genes | Zendy

Thomas Fournier | Zendy; J.-P. Gabriel | Zendy; Christian Mazza | Zendy; Jérôme Pasquier | Zendy; José Luis Galbete | Zendy; Nicolas Mermod | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Steady-state expression of self-regulated genes

Author(s) -

Thomas Fournier,

J.-P. Gabriel,

Christian Mazza,

Jérôme Pasquier,

José Luis Galbete,

Nicolas Mermod

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm490

Subject(s) - expression (computer science) , computer science , gene regulatory network , steady state (chemistry) , gene , gene expression , state (computer science) , stochastic modelling , computational biology , genetic network , biological network , monte carlo method , regulation of gene expression , biology , biological system , mathematics , algorithm , genetics , chemistry , statistics , programming language

Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research