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A point process driven multiple change point model: a robust resistant approach. (English) Zbl 1168.92017

Summary: Helicases are a class of enzymes involved in Ribonucleic Acid (RNA) metabolism. In this work, a statistical method is proposed to analyze the individual mechanistic cycle of these motor proteins which are crucial to the understanding of their cellular functions. The RNA unwinding by NS3 helicase is hypothesized to occur in a series of discrete steps and the steps themselves occurring in accordance to an underlying point process. A point process driven multiple change point model is proposed to model the RNA unwinding mechanism. The methods are portable to other areas of applications as well. Algorithms based on robust-resistant statistical procedures are proposed to detect the change points. Both sequential and a posteriori change point models are considered. The relevant parameters of interest are estimated using a maximum likelihood approach. Simulations are performed to assess the performance of the methodology.

MSC:

92C40 Biochemistry, molecular biology
92C37 Cell biology
62P10 Applications of statistics to biology and medical sciences; meta analysis
60G55 Point processes (e.g., Poisson, Cox, Hawkes processes)
60G35 Signal detection and filtering (aspects of stochastic processes)
92-08 Computational methods for problems pertaining to biology

Software:

ROBETH; R
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References:

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