miRTRAP statistics

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Citations per year

Number of citations per year for the bioinformatics software tool miRTRAP
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Tool usage distribution map

This map represents all the scientific publications referring to miRTRAP per scientific context
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miRTRAP specifications

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Unique identifier OMICS_14628
Name miRTRAP
Alternative name miRNA Tests for Read Analysis and Prediction
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability No
Maintained No

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Publication for miRNA Tests for Read Analysis and Prediction

miRTRAP citations

 (7)
library_books

Detecting and characterizing microRNAs of diverse genomic origins via miRvial

2017
Nucleic Acids Res
PMCID: 5716067
PMID: 29036674
DOI: 10.1093/nar/gkx834

[…] itivity in predicting miRNAs in both animals and plants. For example, miRvial has sensitivities of 90.32% and 88.67% in predicting mouse and fruitfly miRNAs, respectively. In comparison, miRDeep2 and miRTRAP have slightly lower sensitivities than miRvial in mouse and fruitfly miRNAs, but fell short to a large extent in algae miRNAs (96% of miRvial versus 45% of miRDeep2 and 33% of miRTRAP, Figure […]

library_books

Genome wide survey of miRNAs and their evolutionary history in the ascidian, Halocynthia roretzi

2017
BMC Genomics
PMCID: 5399378
PMID: 28427349
DOI: 10.1186/s12864-017-3707-5

[…] longing to 285 families, were previously identified and deposited in miRBase. These miRNAs were predicted from miRNA-seq data collected from Ciona embryos at the gastrula and larval stages, using the miRTRAP computational program [], a method that makes no hypothesis on the evolutionary conservation of these candidates. Of these 348 miRNAs, only 47 miRNAs, belonging to 36 families, were widely con […]

library_books

A Comprehensive Prescription for Plant miRNA Identification

2017
Front Plant Sci
PMCID: 5258749
PMID: 28174574
DOI: 10.3389/fpls.2016.02058

[…] ether with their sequential isoforms, isomiRs (Bartel, ; Wang et al., ; Budak et al., ; Budak and Kantar, ).There are several tools for in silico miRNA identification such as miRanalyzer, miR-PREFeR, miRTRAP, miRLocator, and MIReNA (Hendrix et al., ; Mathelier and Carbone, ; Hackenberg et al., ; Lei and Sun, ; Cui et al., ). Majority of these methods rely on the sequence information of previously […]

library_books

Computational Prediction of miRNA Genes from Small RNA Sequencing Data

2015
Front Bioeng Biotechnol
PMCID: 4306309
PMID: 25674563
DOI: 10.3389/fbioe.2015.00007

[…] miRTRAP uses a rules-based approach with two filtering steps (Hendrix et al., ). In the first one, all candidate miRNAs whose structure and read signatures do not conform to Drosha/Dicer processing ar […]

library_books

Impact of the Genetic Background on the Composition of the Chicken Plasma MiRNome in Response to a Stress

2014
PLoS One
PMCID: 4256448
PMID: 25473826
DOI: 10.1371/journal.pone.0114598

[…] lamus, heart, kidney, liver, lung, breast-muscle, sciatic nerve, proventriculus and spleen. The database contains mappings to known miRNAs (miRBase v20; ) as well as novel miRNAs identified using the miRTrap software for each tissue. A FPKM (fragments per kilobase per million mapped reads) quantitative value is provided for each miRNA feature in each tissue. […]

library_books

Discovery of Novel MicroRNAs in Rat Kidney Using Next Generation Sequencing and Microarray Validation

2012
PLoS One
PMCID: 3314633
PMID: 22470567
DOI: 10.1371/journal.pone.0034394

[…] Several tools have been widely used for miRNA transcriptomic analysis of NGS data to discover novel miRNAs, including miRDeep , , , , miRDeep2 , miRDeep-p , miRanalyzer , , , miRExpress , deepBase , miRTRAP , mirTools , SSCprofilter , , mirExplorer , and MIReNA . Although these tools use different algorithms to predict novel miRNAs, they share the same two basic principles: 1) mapping of the read […]


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miRTRAP institution(s)
Department of Molecular and Cell Biology, Division of Genetics, Genomics and Development, Center for Integrative Genomics, University of California, Berkeley, CA, USA
miRTRAP funding source(s)
This work was supported by NIH grant 5R24GM075049-04.

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