Evidence map›Paper›PMID 25889572›Full record

ArticleBMC research notes2015

mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data.

Marie Luise Gebhardt, Arvind Singh Mer, Miguel Angel Andrade-Navarro

Abstract read
In one paragraph

Article in BMC research notes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. [Establishment and gene expression analysis of drug-resistant cell lines in hepatocellular carcinoma induced by sorafenib].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2020
    Article
4 · The record

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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

3 authors.

Marie Luise GebhardtMax Delbrück Center for Molecular Medicine, Berlin, 13125, Germany. marie.gebhardt@mdc-berlin.de.
Arvind Singh MerMax Delbrück Center for Molecular Medicine, Berlin, 13125, Germany. arvind.mer@ki.se.
Miguel Angel Andrade-NavarroMax Delbrück Center for Molecular Medicine, Berlin, 13125, Germany. andrade@uni-mainz.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOver-representation of predicted miRNA targets in sets of genes regulated by a given transcription factor (e.g. as defined by ChIP-sequencing experiments) helps to identify biologically relevant miRNA targets and is useful to get insight into post-transcriptional regulation.

findingsTo facilitate the application of this approach we have created the mBISON web-application. mBISON calculates the significance of over-representation of miRNA targets in a given non-ranked gene set. The gene set can be specified either by a list of genes or by one or more ChIP-seq datasets followed by a user-defined peak-gene association procedure. mBISON is based on predictions from TargetScan and uses a randomization step to calculate False-Discovery-Rates for each miRNA, including a correction for gene set specific properties such as 3'UTR length. The tool can be accessed from the following web-resource: http://cbdm.mdc-berlin.de/~mgebhardt/cgi-bin/mbison/home .

conclusionmBISON is a web-application that helps to extract functional information about miRNAs from gene lists, which is in contrast to comparable applications easy to use by everyone and can be applied on ChIP-seq data directly.

Indexed as

InternetChromatin ImmunoprecipitationMicroRNAsSequence Analysis, RNAMicroRNAs

Identifiers

PMID25889572
PMCPMC4404576

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