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Analysis of deterministic cyclic gen...

Ahsen, Mehmet Eren.

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Analysis of deterministic cyclic gene regulatory network models with delays

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysis of deterministic cyclic gene regulatory network models with delays/ by Mehmet Eren Ahsen, Hitay Ozbay, Silviu-Iulian Niculescu.
Author:	Ahsen, Mehmet Eren.
other author:	Ozbay, Hitay.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xiii, 94 p. :ill., digital ;24 cm.
[NT 15003449]:	Preface -- Introduction -- Basic Tools from Systems and Control Theory -- Functions with Negative Schwarzian Derivatives -- Deterministic ODE-Based Model with Time Delay -- Gene Regulatory Networks under Negative Feedback -- Gene Regulatory Networks under Positive Feedback -- Summary and Concluding Remarks -- References.
Contained By:	Springer eBooks
Subject:	Gene regulatory networks - Mathematical models. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-15606-4
ISBN:	9783319156064 (electronic bk.)

Analysis of deterministic cyclic gene regulatory network models with delays
Ahsen, Mehmet Eren.

Analysis of deterministic cyclic gene regulatory network models with delays[electronic resource] /by Mehmet Eren Ahsen, Hitay Ozbay, Silviu-Iulian Niculescu. - Cham :Springer International Publishing :2015. - xiii, 94 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering, Control, automation and robotics,2191-8112. - SpringerBriefs in electrical and computer engineering.Control, automation and robotics..

Preface -- Introduction -- Basic Tools from Systems and Control Theory -- Functions with Negative Schwarzian Derivatives -- Deterministic ODE-Based Model with Time Delay -- Gene Regulatory Networks under Negative Feedback -- Gene Regulatory Networks under Positive Feedback -- Summary and Concluding Remarks -- References.

This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

ISBN: 9783319156064 (electronic bk.)

Standard No.: 10.1007/978-3-319-15606-4doiSubjects--Topical Terms:

2134688
Gene regulatory networks
--Mathematical models.

LC Class. No.: QH450

Dewey Class. No.: 572.865015118

Analysis of deterministic cyclic gene regulatory network models with delays
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505 0 $a Preface -- Introduction -- Basic Tools from Systems and Control Theory -- Functions with Negative Schwarzian Derivatives -- Deterministic ODE-Based Model with Time Delay -- Gene Regulatory Networks under Negative Feedback -- Gene Regulatory Networks under Positive Feedback -- Summary and Concluding Remarks -- References.
520 $a This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.
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