Abstract
Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented.
Keywords: Gene expression data, Genome-wide inference, Computational model, Transcriptional regulatory network, Reverse engineering.
Graphical Abstract
Current Genomics
Title:Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data
Volume: 16 Issue: 1
Author(s): Zhi-Ping Liu
Affiliation:
Keywords: Gene expression data, Genome-wide inference, Computational model, Transcriptional regulatory network, Reverse engineering.
Abstract: Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented.
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Cite this article as:
Liu Zhi-Ping, Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data, Current Genomics 2015; 16 (1) . https://dx.doi.org/10.2174/1389202915666141110210634
DOI https://dx.doi.org/10.2174/1389202915666141110210634 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
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