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

Journal: Artificial intelligence in medicine

Published Date: Jul 18, 2017

Abstract

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

Authors

Utku Erdogdu

Department of Computer Engineering, Middle East Technical University, Ankara, Turkey. Electronic address: utku@ceng.metu.edu.tr.
Faruk Polat
Reda Alhajj

University of Calgary, Canada; Istanbul Medipol University, Turkey; University of Southern Denmark, Denmark. Electronic address: alhajj@ucalgary.ca.

Keywords

Artificial Intelligence Computational Biology Databases, Genetic Gene Expression Profiling Gene Expression Regulation, Neoplastic Gene Regulatory Networks Humans Markov Chains Melanoma Skin Neoplasms Transcriptome

External Resources

View on PubMed Access via DOI PubMed (28733120)

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

Abstract

Authors

Keywords

External Resources

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