期刊名称：Computational and Structural Biotechnology Journal
印刷版ISSN：2001-0370
出版年度：2014
卷号：11
期号：19
页码：123-130
DOI：10.1016/j.csbj.2014.09.004
语种：
出版社：Computational and Structural Biotechnology Journal
摘要：A paragraph from the highlights of “Transcriptomics: Throwing light on dark matter” by L. Flintoft (Nature Reviews Genetics 11, 455, 2010), says: “Reports over the past few years of extensive transcription throughout eukaryotic genomes have led to considerable excitement. However, doubts have been raised about the methods that have detected this pervasive transcription and about how much of it is functional.” Since the appearance of the ENCODE project and due to follow-up work, a shift from the pervasive transcription observed from RNA-Seq data to its functional validation is gradually occurring. However, much less attention has been turned to the problem of deciphering the complexity of transcriptome data, which determines uncertainty with regard to identification, quantification and differential expression of genes and non-coding RNAs. The aim of this mini-review is to emphasize transcriptome-related problems of direct and inverse nature for which novel inference approaches are needed.
