miRRim statistics

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Citations per year

Number of citations per year for the bioinformatics software tool miRRim
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Protocols

miRRim specifications

Information


Unique identifier OMICS_07331
Name miRRim
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 2.0
Stability No
Maintained No

Versioning


No version available

Publications for miRRim

miRRim citations

 (7)
library_books

MatPred: Computational Identification of Mature MicroRNAs within Novel Pre MicroRNAs

2015
Biomed Res Int
PMCID: 4670854
PMID: 26682221
DOI: 10.1155/2015/546763

[…] n reported for identifying mature miRNAs from their pre-miRNA transcripts. For instance, MiRmat [] was designed to predict Drosha and Dicer cleavage sites in vertebrates using a Random Forest method. MiRRim2 [] is designed for predicting human mature miRNA candidates using a conditional random fields (CRFs) method, based on evolutionary conserved features upstream of Drosha cleavage sites. MatureB […]

library_books

Bioinformatic tools for microRNA dissection

2015
Nucleic Acids Res
PMCID: 4705652
PMID: 26578605
DOI: 10.1093/nar/gkv1221

[…] ndidate sequences. Prediction of conserved and non-conserved miRNA genes is also possible by adjusting the filtering criteria. Use of appropriate training data sets allows application to all species. MiRRim () is another HMM-based tool that considers both evolutionary and secondary structure features of miRNA genes to achieve high-performance identification of new human miRNAs, in particular those […]

call_split

MicroRNAs: New Biomarkers for Diagnosis, Prognosis, Therapy Prediction and Therapeutic Tools for Breast Cancer

2015
Theranostics
PMCID: 4508501
PMID: 26199650
DOI: 10.7150/thno.11543
call_split See protocol

[…] th positive and negative training sets . Many tools of machine learning-based approaches for miRNA target prediction are currently available, e.g., HHMMiR , PicTar , MiRFinder , RNAmicro , , ProMiR , MiRRim , BayesMiRNAFind , and SSCprofiler .Other computational algorithms use approaches different from machine learning. The TargetScan algorithm was the first miRNA target prediction tool for human […]

library_books

A Review of Computational Tools in microRNA Discovery

2013
Front Genet
PMCID: 3654206
PMID: 23720668
DOI: 10.3389/fgene.2013.00081

[…] be applied to NGS data. Besides sequence conservation, it utilizes miRNA features such as secondary structure, employing a machine-learning algorithm to find miRNA precursors. This tool is similar to MiRRim in that it considers structure and conservation with an HMM algorithm (Oulas et al., ). […]

library_books

A framework for automated enrichment of functionally significant inverted repeats in whole genomes

2010
BMC Bioinformatics
PMCID: 3026368
PMID: 20946604
DOI: 10.1186/1471-2105-11-S6-S20

[…] es, miRSeeker applies mutation patterns that are typical of miRNAs, and miRScan identifies those structures having features such as symmetric bulges or a highly conserved stem near the terminal loop. miRRim [] represents the evolutionary and secondary structural features of all known miRNA and their surrounding regions with a sequence of multidimensional vectors. It uses these to train hidden Mark […]

library_books

Bone marrow ectopic expression of a non coding RNA in childhood T cell acute lymphoblastic leukemia with a novel t(2;11)(q11.2;p15.1) translocation

2008
Mol Cancer
PMCID: 2579299
PMID: 18947387
DOI: 10.1186/1476-4598-7-80

[…] showed that it contained a high density of stop codons resulting in very short ORFs.We hypothesized that this ncRNA could represent a precursor of an miRNA, but the miRNA prediction table produced by miRRim and a sequence similarity search at miRBase showed no significant matches (data not shown). Similarly, miRNA predictions by ProMiR II and miR-abela did not retrieve any positive results (da […]


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miRRim institution(s)
INTEC Inc., Tokyo, Japan; Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan; Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Chiba, Japan
miRRim funding source(s)
This work was supported partly by a Grant-in-Aid for Scientific Research (A) and the Functional RNA Project of the New Energy and Industrial Technology Development Organization.

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