Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/10225
Title: Clumped-MCEM: Inference for multistep transcriptional processes
Authors: Shetty, K.S.
B, A.
Issue Date: 2019
Citation: Computational Biology and Chemistry, 2019, Vol.81, , pp.16-20
Abstract: Many biochemical events involve multistep reactions. Among them, an important biological process that involves multistep reaction is the transcriptional process. A widely used approach for simplifying multistep reactions is the delayed reaction method. In this work, we devise a model reduction strategy that represents several OFF states by a single state, accompanied by specifying a time delay for burst frequency. Using this model reduction, we develop Clumped-MCEM which enables simulation and parameter inference. We apply this method to time-series data of endogenous mouse glutaminase promoter, to validate the model assumptions and infer the kinetic parameters. Further, we compare efficiency of Clumped-MCEM with state-of-the-art methods Bursty MCEM2 and delay Bursty MCEM. Simulation results show that Clumped-MCEM inference is more efficient for time-series data and is able to produce similar numerical accuracy as state-of-the-art methods Bursty MCEM2 and delay Bursty MCEM in less time. Clumped-MCEM reduces computational cost by 57.58% when compared with Bursty MCEM2 and 32.19% when compared with delay Bursty MCEM. 2019 Elsevier Ltd
URI: http://idr.nitk.ac.in/jspui/handle/123456789/10225
Appears in Collections:1. Journal Articles

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