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Scalable approach for effective control of gene regulatory networks
Date
2010-01-01
Author
Tan, Mehmet
Alhajj, Reda
Polat, Faruk
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Objective: Interactions between genes are realized as gene regulatory networks (GRNs). The control of such networks is essential for investigating issues like different diseases. Control is the process of studying the states and behavior of a given system under different conditions. The system considered in this study is a gene regulatory network (GRN), and one of the most important aspects in the control of GRNs is scalability. Consequently, the objective of this study is to develop a scalable technique that facilitates the control of GRNs.
Subject Keywords
Medicine (miscellaneous)
,
Artificial Intelligence
URI
https://hdl.handle.net/11511/38800
Journal
ARTIFICIAL INTELLIGENCE IN MEDICINE
DOI
https://doi.org/10.1016/j.artmed.2009.10.002
Collections
Department of Computer Engineering, Article