Corrigendum: Transcriptome-Wide Annotation of m⁵C RNA Modifications Using Machine Learning

In the original article, there was an error, the word “reversible” is misleading. A correction has been made to the Abstract and the Introduction, paragraph 2.

Though high-throughput experimental technologies have been developed and applied to profile m⁵C modifications under certain conditions, transcriptome-wide studies of m⁵C modifications are still hindered by the dynamic nature of m⁵C and the lack of computational prediction methods.

Second, because of the dynamic nature of m⁵C (Wang and He, 2014), existing high-throughput sequencing technologies can only capture a snapshot of RNA modifications under certain experimental conditions, and cover just a small fraction of the whole transcriptome of a given sample (Zhou et al., 2016), resulting in the generation of significant numbers of false negatives (non-detected true m⁵C modifications).

The authors apologize for the mistake. This error does not change the scientific conclusions of the article in any way. The original article has been updated.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.