Transient dynamics of genetic regulatory networks.

نویسندگان

  • Matthew R Bennett
  • Dmitri Volfson
  • Lev Tsimring
  • Jeff Hasty
چکیده

We present an approximation scheme for deriving reaction rate equations of genetic regulatory networks. This scheme predicts the timescales of transient dynamics of such networks more accurately than does standard quasi-steady state analysis by introducing prefactors to the ODEs that govern the dynamics of the protein concentrations. These prefactors render the ODE systems slower than their quasi-steady state approximation counterparts. We introduce the method by examining a positive feedback gene regulatory network, and show how the transient dynamics of this network are more accurately modeled when the prefactor is included. Next, we examine the repressilator, a genetic oscillator, and show that the period, amplitude, and bifurcation diagram defining the onset of the oscillations are better estimated by the prefactor method. Finally, we examine the consequences of the method to the dynamics of reduced models of the phage lambda switch, and show that the switching times between the two states is slowed by the presence of the prefactor that arises from protein multimerization and DNA binding.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

H∞ Sampled-Data Controller Design for Stochastic Genetic Regulatory Networks

Artificially regulating gene expression is an important step in developing new treatment for system-level disease such as cancer. In this paper, we propose a method to regulate gene expression based on sampled-data measurements of gene products concentrations. Inherent noisy behaviour of Gene regulatory networks are modeled with stochastic nonlinear differential equation. To synthesize feed...

متن کامل

I-13: Transcriptome Dynamics of Human and Mouse Preimplantation Embryos Revealed by Single Cell RNA-Sequencing

Background: Mammalian preimplantation development is a complex process involving dramatic changes in the transcriptional architecture. However, it is still unclear about the crucial transcriptional network and key hub genes that regulate the proceeding of preimplantation embryos. Materials and Methods: Through single-cell RNAsequencing (RNA-seq) of both human and mouse preimplantation embryos, ...

متن کامل

Pareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms

A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...

متن کامل

Transient Perturbations on Scale-Free Boolean Networks with Topology Driven Dynamics

Taking into account the topology of genetic regulatory networks and abstracting recent findings about them, we investigate the behavior of a new, more biologically plausible, variation of the original Random Boolean Network paradigm. We study the dynamics of Boolean networks with scale-free structures, that evolve in time using a semi-synchronous topology-driven update scheme. Simulating statis...

متن کامل

Effects of Transcriptional Pausing on Gene Expression Dynamics

Stochasticity in gene expression affects many cellular processes and is a source of phenotypic diversity between genetically identical individuals. Events in elongation, particularly RNA polymerase pausing, are a source of this noise. Since the rate and duration of pausing are sequence-dependent, this regulatory mechanism of transcriptional dynamics is evolvable. The dependency of pause propens...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Biophysical journal

دوره 92 10  شماره 

صفحات  -

تاریخ انتشار 2007