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Updated: Jun 23, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
A point process driven multiple change point model: a robust resistant approach
1Department of Biostatistics and Anesthesiology, Columbia University Medical Center, PH5-505, New York, NY 10032, USA. sarunajadai@columbia.edu
Abstract:
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.
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