Computational inference of gene regulatory networks: Approaches, limitations and opportunities

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• 作者：Michael Banf ; ^{michael.banf@gmx.net} ; Seung Y. Rhee ; ^{srhee@carnegiescience.edu}
• 关键词：Computational systems biology ; Gene regulatory network inference ; Machine learning ; Heterogeneous data integration ; Gene network evaluation
• 刊名：Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：1860
• 期：1
• 页码：41-52
• 全文大小：960 K
• 卷排序：1860

文摘

The basic concepts and methodologies used for gene expression based regulatory network inference are introduced The limitations of network inference based on transcriptional datasets only are described The data types and strategies used for integrative gene regulatory network inference and causal link prediction are presented The caveats and solutions for the selection of statistically and biologically relevant regulatory interactions are discussed