Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks

Nayely Velez-Cruz; Bahman Moraffah; Antonia Papandreou-Suppappola

doi:10.1109/IEEECONF53345.2021.9723310

Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks

Nayely Velez-Cruz, Bahman Moraffah, Antonia Papandreou-Suppappola

Engineering, Ira A. Fulton Schools of (IAFSE)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

A key challenge in inferring the structure and dynamics of gene regulatory networks is the representation of various sources of stochasticity in mathematical models. In this work, we propose a modified stochastic Michaelis-Menten model to better capture the complex molecular mechanisms involved in gene regulation. We show that Bayesian sequential inference methods can be used to estimate gene expression values when utilizing this complex model. We also study the effect of various types of noise sources that arise from biological reactions and environmental fluctuations. We also extend these models to include time-varying kinetic order parameters so that they may be used for inference of time-varying gene regulatory networks.

Original language	English (US)
Title of host publication	55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	568-572
Number of pages	5
ISBN (Electronic)	9781665458283
DOIs	https://doi.org/10.1109/IEEECONF53345.2021.9723310
State	Published - 2021
Event	55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 - Virtual, Pacific Grove, United States Duration: Oct 31 2021 → Nov 3 2021

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2021-October
ISSN (Print)	1058-6393

Conference

Conference	55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
Country/Territory	United States
City	Virtual, Pacific Grove
Period	10/31/21 → 11/3/21

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/IEEECONF53345.2021.9723310

Cite this

Velez-Cruz, N., Moraffah, B., & Papandreou-Suppappola, A. (2021). Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks. In M. B. Matthews (Ed.), 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 (pp. 568-572). (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2021-October). IEEE Computer Society. https://doi.org/10.1109/IEEECONF53345.2021.9723310

Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks. / Velez-Cruz, Nayely; Moraffah, Bahman; Papandreou-Suppappola, Antonia.
55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021. ed. / Michael B. Matthews. IEEE Computer Society, 2021. p. 568-572 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2021-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Velez-Cruz, N, Moraffah, B & Papandreou-Suppappola, A 2021, Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks. in MB Matthews (ed.), 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021. Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2021-October, IEEE Computer Society, pp. 568-572, 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021, Virtual, Pacific Grove, United States, 10/31/21. https://doi.org/10.1109/IEEECONF53345.2021.9723310

Velez-Cruz N, Moraffah B, Papandreou-Suppappola A. Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks. In Matthews MB, editor, 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021. IEEE Computer Society. 2021. p. 568-572. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/IEEECONF53345.2021.9723310

Velez-Cruz, Nayely ; Moraffah, Bahman ; Papandreou-Suppappola, Antonia. / Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks. 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021. editor / Michael B. Matthews. IEEE Computer Society, 2021. pp. 568-572 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks

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