Evidence map›Paper›PMID 24771340›Full record

ArticleNucleic acids research2014

NetVenn: an integrated network analysis web platform for gene lists.

Yi Wang, Roger Thilmony, Yong Q Gu

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

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

19 citing papers in PubMed.

  1. List2Net: Linking multiple lists of biological data in a network context.Computational and structural biotechnology journal · 2024
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  18. Predicting CK2 beta-dependent substrates using linear patterns.Biochemistry and biophysics reports · 2015
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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

3 authors.

Yi WangUSDA-ARS, Western Regional Research Center, Genomics and Gene Discovery Research Unit, Albany, CA 94710, USA Department of Plant Sciences, University of California, Davis, CA 95616, USA Yong.Gu@ars.usda.gov.
Roger ThilmonyUSDA-ARS, Western Regional Research Center, Crop Improvement Research Unit, Albany, CA 94710, USA.
Yong Q GuUSDA-ARS, Western Regional Research Center, Genomics and Gene Discovery Research Unit, Albany, CA 94710, USA Yong.Gu@ars.usda.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many lists containing biological identifiers, such as gene lists, have been generated in various genomics projects. Identifying the overlap among gene lists can enable us to understand the similarities and differences between the data sets. Here, we present an interactome network-based web application platform named NetVenn for comparing and mining the relationships among gene lists. NetVenn contains interactome network data publically available for several species and supports a user upload of customized interactome network data. It has an efficient and interactive graphic tool that provides a Venn diagram view for comparing two to four lists in the context of an interactome network. NetVenn also provides a comprehensive annotation of genes in the gene lists by using enriched terms from multiple functional databases. In addition, it allows for mapping the gene expression data, providing information of transcription status of genes in the network. The power graph analysis tool is integrated in NetVenn for simplified visualization of gene relationships in the network. NetVenn is freely available at http://probes.pw.usda.gov/NetVenn or http://wheat.pw.usda.gov/NetVenn.

Indexed as

Gene Regulatory NetworksSoftwareAnimalsArabidopsisGene ExpressionHumansInternetMiceMolecular Sequence AnnotationPlant RootsProtein Interaction MappingRats

Identifiers

PMID24771340
PMCPMC4086115

What OpenQuestion holds

Textmetadata
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.