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Reverse Engineering Genetic Networks Using Nonlinear Saturation Kinetics
2019
Biosystems (Amsterdam. Print)
A gene regulatory network (GRN) represents a set of genes along with their regulatory interactions. Cellular behavior is driven by genetic level interactions. Dynamics of such systems show nonlinear saturation kinetics which can be best modeled by Michaelis-Menten (MM) and Hill equations. Although MM equation is being widely used for modeling biochemical processes, it has been applied rarely for reverse engineering GRNs. In this paper, we develop a complete framework for a novel model for GRN
doi:10.1016/j.biosystems.2019.103977
pmid:31185246
fatcat:z7mmg7k37jcxbilnk2gd3ei33e