Evidence map›Paper›PMID 19821977›Full record

ArticleBMC bioinformatics2009

miRExpress: analyzing high-throughput sequencing data for profiling microRNA expression.

Wei-Chi Wang, Feng-Mao Lin, Wen-Chi Chang, Kuan-Yu Lin, Hsien-Da Huang, Na-Sheng Lin

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
5.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

114 citing papers in PubMed, 186 citations in OpenAlex.

  1. Review
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  5. Hepatitis B Virus and microRNAs: A Bioinformatics Approach.International journal of molecular sciences · 2023
    Review
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  16. MicroRNAs Regulating Autophagy in Neurodegeneration.Advances in experimental medicine and biology · 2021
    Article
  17. Transfer RNA fragments replace microRNA regulators of the cholinergic poststroke immune blockade.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  18. Article
  19. Article
  20. Article

54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Wei-Chi WangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan, Republic of China. canser.bi95g@nctu.edu.tw
Feng-Mao Lin
Wen-Chi Chang
Kuan-Yu Lin
Hsien-Da Huang
Na-Sheng Lin
National Yang Ming Chiao Tung University · TWInstitute of Plant and Microbial Biology, Academia Sinica · TWNational Cheng Kung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicroRNAs (miRNAs), small non-coding RNAs of 19 to 25 nt, play important roles in gene regulation in both animals and plants. In the last few years, the oligonucleotide microarray is one high-throughput and robust method for detecting miRNA expression. However, the approach is restricted to detecting the expression of known miRNAs. Second-generation sequencing is an inexpensive and high-throughput sequencing method. This new method is a promising tool with high sensitivity and specificity and can be used to measure the abundance of small-RNA sequences in a sample. Hence, the expression profiling of miRNAs can involve use of sequencing rather than an oligonucleotide array. Additionally, this method can be adopted to discover novel miRNAs.

resultsThis work presents a systematic approach, miRExpress, for extracting miRNA expression profiles from sequencing reads obtained by second-generation sequencing technology. A stand-alone software package is implemented for generating miRNA expression profiles from high-throughput sequencing of RNA without the need for sequenced genomes. The software is also a database-supported, efficient and flexible tool for investigating miRNA regulation. Moreover, we demonstrate the utility of miRExpress in extracting miRNA expression profiles from two Illumina data sets constructed for the human and a plant species.

conclusionWe develop miRExpress, which is a database-supported, efficient and flexible tool for detecting miRNA expression profile. The analysis of two Illumina data sets constructed from human and plant demonstrate the effectiveness of miRExpress to obtain miRNA expression profiles and show the usability in finding novel miRNAs.

Indexed as

SoftwareComputational BiologyGene Expression ProfilingGene Expression RegulationGenome, HumanGenome, PlantHumansMicroRNAsSequence Analysis, RNAMicroRNAs

Identifiers

PMID19821977
PMCPMC2767369
OpenAlexW2014208702

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.