Dicer cleavage site detection software tools | Non-coding RNA data analysis
Dicer, an RNase III enzyme, plays a vital role in the processing of pre-miRNAs for generating the miRNAs. The structural and sequence features on pre-miRNA which can facilitate position and efficiency of cleavage are not well known. A precise cleavage by Dicer is crucial because an inaccurate processing can produce miRNA with different seed regions which can alter the repertoire of target genes.
A webserver to predict Dicer cleavage sites in pre-miRNA. PHDcleav can be used to investigate functional consequences of genetic variations/SNPs in miRNA on Dicer cleavage site, and gene silencing. it would also be useful in the discovery of miRNAs in human genome and design of Dicer specific pre-miRNAs for potent gene silencing. This tool can also be used to optimize and design more accurate site for Dicer cleavage in the shRNA/amiRNA.
A method for predicting Dicer cleavage sites. LBSizeCleav offers a feature space mapping by introducing the length of a loop/bulge structure into the algorithm. The binary pattern of LBSizeCleav is an extension of PHDCleav. To evaluate this method, 810 empirically validated sequences of human pre-miRNAs were used and fivefold cross-validation were performed. In both 5p and 3p arms of pre-miRNAs, LBSizeCleav showed greater prediction accuracy than PHDCleav did. This result suggests that the length of loop/bulge structures is useful for prediction of Dicer cleavage sites.
Predicts 5' Drosha processing sites in hairpins that are candidate miRNAs. Microprocessor SVM correctly predicts the processing site for 50% of known human 5' miRNAs, and 90% of its predictions are within two nucleotides of the true site. The Microprocessor SVM shows good performance when separating miRNAs from random hairpins, despite that SVM was not trained for this purpose.
Discover our proposed protocols. They are easy to use or edit to meet your needs.