ArticleBMC bioinformatics2013
PHDcleav: a SVM based method for predicting human Dicer cleavage sites using sequence and secondary structure of miRNA precursors.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- DiCleave: a deep learning model for predicting human Dicer cleavage sites.BMC bioinformatics · 2024Article
- DecipheringEpigenomics · 2024Article
- Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets.Functional & integrative genomics · 2023Review
- Article
- BARD1 mystery: tumor suppressors are cancer susceptibility genes.BMC cancer · 2022Review
- ReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites.BMC bioinformatics · 2021Article
- Predicting Drosha and Dicer Cleavage Sites with DeepMirCut.Frontiers in molecular biosciences · 2021Article
- iMPTCE-Hnetwork: A Multilabel Classifier for Identifying Metabolic Pathway Types of Chemicals and Enzymes with a Heterogeneous Network.Computational and mathematical methods in medicine · 2021Article
- Identifying the Signatures and Rules of Circulating Extracellular MicroRNA for Distinguishing Cancer Subtypes.Frontiers in genetics · 2021Article
- Investigating the pathogenic SNPs in BLM helicase and their biological consequences by computational approach.Scientific reports · 2020Article
- A Comprehensive Analysis ofFrontiers in genetics · 2020Article
- Identifying Circular RNA and Predicting Its Regulatory Interactions by Machine Learning.Frontiers in genetics · 2020Article
- Trends in the development of miRNA bioinformatics tools.Briefings in bioinformatics · 2019Review
- FLOating-Window Projective Separator (FloWPS): A Data Trimming Tool for Support Vector Machines (SVM) to Improve Robustness of the Classifier.Frontiers in genetics · 2018Article
- RNA stem structure governs coupling of dicing and gene silencing in RNA interference.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Yellow Fever Virus, but Not Zika Virus or Dengue Virus, Inhibits T-Cell Receptor-Mediated T-Cell Function by an RNA-Based Mechanism.The Journal of infectious diseases · 2017Article
- Alternative splicing of the OCC-1 gene generates three splice variants and a novel exonic microRNA, which regulate the Wnt signaling pathway.RNA (New York, N.Y.) · 2017Article
- MicroRNA and Transcription Factor: Key Players in Plant Regulatory Network.Frontiers in plant science · 2017Review
- LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length.BMC bioinformatics · 2016Article
- ZIKV - CDB: A Collaborative Database to Guide Research Linking SncRNAs and ZIKA Virus Disease Symptoms.PLoS neglected tropical diseases · 2016Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundDicer, 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.
resultsIn this study, a novel method has been developed to predict Dicer cleavage sites on pre-miRNAs using Support Vector Machine. We used the dataset of experimentally validated human miRNA hairpins from miRBase, and extracted fourteen nucleotides around Dicer cleavage sites. We developed number of models using various types of features and achieved maximum accuracy of 66% using binary profile of nucleotide sequence taken from 5p arm of hairpin. The prediction performance of Dicer cleavage site improved significantly from 66% to 86% when we integrated secondary structure information. This indicates that secondary structure plays an important role in the selection of cleavage site. All models were trained and tested on 555 experimentally validated cleavage sites and evaluated using 5-fold cross validation technique. In addition, the performance was also evaluated on an independent testing dataset that achieved an accuracy of ~82%.
conclusionBased on this study, we developed a webserver PHDcleav (http://www.imtech.res.in/raghava/phdcleav/) to predict Dicer cleavage sites in pre-miRNA. This tool can be used to investigate functional consequences of genetic variations/SNPs in miRNA on Dicer cleavage site, and gene silencing. Moreover, it would also be useful in the discovery of miRNAs in human genome and design of Dicer specific pre-miRNAs for potent gene silencing.
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