Employing decomposable partially observable Markov decision processes to control gene regulatory networks

Date

2017-11-01

Author

Erdogdu, Utku
Polat, Faruk
Alhajj, Reda

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Objective: Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs).

Subject Keywords

Gene regulatory networks, Control of gene regulatory networks, Processes, Partially Observable Markov Decision

URI

https://hdl.handle.net/11511/44975

Journal

ARTIFICIAL INTELLIGENCE IN MEDICINE

DOI

https://doi.org/10.1016/j.artmed.2017.06.007

Collections

Department of Computer Engineering, Article

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Partially Observable Gene Regulatory Network Control Without a Boundary on Horizon Erdogdu, Utku; Polat, Faruk; Alhajj, Reda (2012-11-09) Gene regulatory networks (GRNs) govern the protein transcription process in the cell and interactions among genes play a vital role in determining the biosynthesis rate of proteins. By using intervention techniques discovered by biological research it is possible to control a GRN, thus promoting or demoting the expression rate of a certain gene. In this work, this control task is studied in a partially observable setting where interventions lack perfect knowledge of the expression level of all genes. Moreov...
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Citation Formats

U. Erdogdu, F. Polat, and R. Alhajj, “Employing decomposable partially observable Markov decision processes to control gene regulatory networks,” ARTIFICIAL INTELLIGENCE IN MEDICINE, pp. 14–34, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/44975.