Experimental detection and validation of miRNAs is a tedious, time-consuming, and expensive process. Computational methods for miRNA gene detection are being developed so that the number of candidates that need experimental validation can be reduced to a manageable amount. Computational methods involve homology-based and ab inito algorithms. Both approaches are dependent on positive and negativ...

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent release...

The avalanche of next generation sequencing data has led to a rapid increase of annotated microRNAs in the last few years. Many of them are specific to individual species or rather narrow clades. A closer inspection of the current version of miRBase shows that dozens of entries conflict with other ncRNAs, in particular snoRNAs. With few exceptions, these cases show little similarities to canoni...

MicroRNAs (miRNAs) are a class of 20-23 nucleotide small RNAs that regulate gene expression post-transcriptionally in animals and plants. Annotation of miRNAs by the miRNA database (miRBase) has largely relied on computational approaches. As a result, many miRBase entries lack experimental validation, and discrepancies between miRBase annotation and actual miRNA sequences are often observed. In...