Stochastic models for studying the degredation of mRNA molecules

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

Abstract

Message RNA (mRNA) is the template for protein synthesis. It carries information from DNA in the nucleus to the ribosome sites of protein synthesis in the cell. The turnover process of mRNA is a chemical event with multiple small step reactions; and the degradation of mRNA molecules is an important step in gene expression. A number of mathematical models have been proposed to study the dynamics of mRNA turnover, ranging from a one-step first order reaction model to the linear multicomponent models. Although the linear multicomponent models provide detailed dynamics of mRNA degradation, the simple first-order reaction model has been widely used in mathematical modelling of genetic regulatory networks. To illustrate the difference between these models, we first considered a stochastic model based on the multicomponent model. Then a simpler linear chain stochastic model was proposed to approximate the linear multicomponent model. We also discussed the delayed one-step reaction models with different types of time delay, including the constant delay, exponentially distributed delay and Erlang distributed delay. The comparison study suggested that the one-step reaction models failed to realize the dynamics of mRNA turnover accurately. Therefore more sophisticated one-step reaction models are needed to study the dynamics of mRNA degradation.
Original languageEnglish
Title of host publicationProceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011)
EditorsFang-Xiang Wu, Mohammed Zaki, Shinichi Morishita, Yi Pan, Stephen Wong, Anastasia Christianson, Xiaohu Hu
Place of PublicationLos Alimos USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages167 - 172
Number of pages6
ISBN (Print)9780769545745
DOIs
Publication statusPublished - 2011
EventIEEE International Conference on Bioinformatics and Biomedicine 2011 - Atlanta, United States of America
Duration: 12 Nov 201115 Nov 2011

Conference

ConferenceIEEE International Conference on Bioinformatics and Biomedicine 2011
Abbreviated titleBIBM 2011
CountryUnited States of America
CityAtlanta
Period12/11/1115/11/11

Cite this

Tian, T. (2011). Stochastic models for studying the degredation of mRNA molecules. In F-X. Wu, M. Zaki, S. Morishita, Y. Pan, S. Wong, A. Christianson, & X. Hu (Eds.), Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011) (pp. 167 - 172). Los Alimos USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BIBM.2011.100
Tian, Tianhai. / Stochastic models for studying the degredation of mRNA molecules. Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011). editor / Fang-Xiang Wu ; Mohammed Zaki ; Shinichi Morishita ; Yi Pan ; Stephen Wong ; Anastasia Christianson ; Xiaohu Hu. Los Alimos USA : IEEE, Institute of Electrical and Electronics Engineers, 2011. pp. 167 - 172
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title = "Stochastic models for studying the degredation of mRNA molecules",
abstract = "Message RNA (mRNA) is the template for protein synthesis. It carries information from DNA in the nucleus to the ribosome sites of protein synthesis in the cell. The turnover process of mRNA is a chemical event with multiple small step reactions; and the degradation of mRNA molecules is an important step in gene expression. A number of mathematical models have been proposed to study the dynamics of mRNA turnover, ranging from a one-step first order reaction model to the linear multicomponent models. Although the linear multicomponent models provide detailed dynamics of mRNA degradation, the simple first-order reaction model has been widely used in mathematical modelling of genetic regulatory networks. To illustrate the difference between these models, we first considered a stochastic model based on the multicomponent model. Then a simpler linear chain stochastic model was proposed to approximate the linear multicomponent model. We also discussed the delayed one-step reaction models with different types of time delay, including the constant delay, exponentially distributed delay and Erlang distributed delay. The comparison study suggested that the one-step reaction models failed to realize the dynamics of mRNA turnover accurately. Therefore more sophisticated one-step reaction models are needed to study the dynamics of mRNA degradation.",
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Tian, T 2011, Stochastic models for studying the degredation of mRNA molecules. in F-X Wu, M Zaki, S Morishita, Y Pan, S Wong, A Christianson & X Hu (eds), Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011). IEEE, Institute of Electrical and Electronics Engineers, Los Alimos USA, pp. 167 - 172, IEEE International Conference on Bioinformatics and Biomedicine 2011, Atlanta, United States of America, 12/11/11. https://doi.org/10.1109/BIBM.2011.100

Stochastic models for studying the degredation of mRNA molecules. / Tian, Tianhai.

Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011). ed. / Fang-Xiang Wu; Mohammed Zaki; Shinichi Morishita; Yi Pan; Stephen Wong; Anastasia Christianson; Xiaohu Hu. Los Alimos USA : IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 167 - 172.

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

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AB - Message RNA (mRNA) is the template for protein synthesis. It carries information from DNA in the nucleus to the ribosome sites of protein synthesis in the cell. The turnover process of mRNA is a chemical event with multiple small step reactions; and the degradation of mRNA molecules is an important step in gene expression. A number of mathematical models have been proposed to study the dynamics of mRNA turnover, ranging from a one-step first order reaction model to the linear multicomponent models. Although the linear multicomponent models provide detailed dynamics of mRNA degradation, the simple first-order reaction model has been widely used in mathematical modelling of genetic regulatory networks. To illustrate the difference between these models, we first considered a stochastic model based on the multicomponent model. Then a simpler linear chain stochastic model was proposed to approximate the linear multicomponent model. We also discussed the delayed one-step reaction models with different types of time delay, including the constant delay, exponentially distributed delay and Erlang distributed delay. The comparison study suggested that the one-step reaction models failed to realize the dynamics of mRNA turnover accurately. Therefore more sophisticated one-step reaction models are needed to study the dynamics of mRNA degradation.

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Tian T. Stochastic models for studying the degredation of mRNA molecules. In Wu F-X, Zaki M, Morishita S, Pan Y, Wong S, Christianson A, Hu X, editors, Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2011). Los Alimos USA: IEEE, Institute of Electrical and Electronics Engineers. 2011. p. 167 - 172 https://doi.org/10.1109/BIBM.2011.100