Download Analysis of Deterministic Cyclic Gene Regulatory Network by Mehmet Eren Ahsen, Hitay Özbay, Silviu-Iulian Niculescu PDF

By Mehmet Eren Ahsen, Hitay Özbay, Silviu-Iulian Niculescu

This short examines a deterministic, ODE-based version for gene regulatory networks (GRN) that includes nonlinearities and time-delayed suggestions. An introductory bankruptcy presents a few insights into molecular biology and GRNs. The mathematical instruments helpful for learning the GRN version are then reviewed, specifically Hill capabilities and Schwarzian derivatives. One bankruptcy is dedicated to the research of GRNs less than damaging suggestions with time delays and a distinct case of a homogenous GRN is taken into account. Asymptotic balance research of GRNs below confident suggestions is then thought of in a separate bankruptcy, during which stipulations resulting in bi-stability are derived. Graduate and complex undergraduate scholars and researchers up to the mark engineering, utilized arithmetic, platforms biology and artificial biology will locate this short to be a transparent and concise creation to the modeling and research of GRNs.

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Extra resources for Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays

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X1 / ¤ 1. x1 / > 1. In the sequel, both situations will be investigated separately. 1 Stability Conditions for GRNs Under Negative Feedback In this chapter, we need a generalized version of the well-known Poincaré– Bendixson Theorem [49]. 1) to be bounded. Our next result establishes such a property. 2. 1), RnC is a positively invariant set and, for any set of initial conditions, the corresponding solution of the system remains bounded. Proof. To prove positive invariance, we only need to check the direction of the vectors on the boundaries of the region RnC D fŒx1 ; x2 ; : : : ; xn T 2 Rn W xi 0 8i D 1; 2; : : : ; ng: The boundaries of the region RnC are just the planes xi D 0.

25) Most of the physical systems that are modeled are casual. 25) is called autonomous. Otherwise, it is called non-autonomous. The 22 2 Basic Tools from Systems and Control Theory GRN model studied in this work represents an autonomous system. Therefore, in this subsection only autonomous systems are considered. t / 2 Rn ; //; 0; f W Rn Rn ! 27), we need to know initial values of the states. t /, for t t0 . 28) An excellent book on the analysis of functional differential equations is [45], and it also contains results on the existence, uniqueness, and continuous dependence of the solutions on initial conditions (these topics are beyond the scope of this manuscript).

20) where i , ai and bi are positive constants and we implicitly assumed the cyclic structure so that PnC1 D P1 , GnC1 D G1 , and neglected the time delay. The Hill function representing inhibition has negative derivative. If n is odd, the overall system will be under negative feedback. On the other hand, if n is even, the system will be under positive feedback. We will perform the analysis for both the negative and positive feedback in the next two chapters. 4 Exercises Problem 1. x/ D 0:1Cx 2 .

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