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Describing Dynamics of Gene Expression Made Easier by PDMP Model




Computational biologists have searched a new way to model certain forms of gene expression accurately, including the body's 24-hour internal clock using a simple analytical framework for random events within a predictable system. Piecewise Deterministic Markov Process (PDMP) model makes it easier to analyze and simulate than earlier models.

It could inform possible design theories for synthetic biologists. Biologists say that it is a natural language to describe the dynamics of eukaryotic gene expression and its implication. It has also been found that PDMP mathematical model accurately describes the random or assumptive dynamics of gene expression in the non-adiabatic regime.  The process is often used where promoter kinetics is slow and fast averaging cannot be done. The latest study suggests that oscillatory dynamics could be more powerful than previous assumption. It is being hoped that it will be proved as a milestone in describing dynamics of gene expression in future. It will also be useful in further researches related to genes.

By: Anuja Arora

Content: https://www.sciencedaily.com/releases/2018/01/180131144555.htm


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