Review article: DATA- AND KNOWLEDGE-BASED MODELING OF GENE REGULATORY NETWORKS: AN UPDATE
作者： Reinhard Guthke , Sebastian G. Henkel , Jörg Linde , Sylvie Schulze
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摘要: Gene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated methods focusing on novel techniques for data acquisition, assessment, interacting species integration prior knowledge. After advance Next-Generation-Sequencing cDNAs derived from RNA samples (RNA-Seq) discuss in detail its application to inference. Furthermore, progress large-scale or even full-genomic as well small-scale condensed review advances evaluation by crowdsourcing. Finally, reflect availability knowledge sources give an outlook gene networks that species, particular pathogen-host interactions.
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