Evidence map›Paper›PMID 21949701›Full record

ArticlePloS one2011

Functional analysis beyond enrichment: non-redundant reciprocal linkage of genes and biological terms.

Celia Fontanillo, Ruben Nogales-Cadenas, Alberto Pascual-Montano, Javier De las Rivas

Abstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
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  10. Elevated COScientific reports · 2019
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  12. ASCT1 (Slc1a4) transporter is a physiologic regulator of brain d-serine and neurodevelopment.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  13. Article
  14. CD4+CD28+KIR+CD11aJournal of autoimmunity · 2018
    Article
  15. Article
  16. Article
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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

4 authors.

Celia FontanilloCancer Research Center (CiC-IBMCC, CSIC/USAL), Campus Miguel de Unamuno, Salamanca, Spain.
Ruben Nogales-Cadenas
Alberto Pascual-Montano
Javier De las Rivas

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional analysis of large sets of genes and proteins is becoming more and more necessary with the increase of experimental biomolecular data at omic-scale. Enrichment analysis is by far the most popular available methodology to derive functional implications of sets of cooperating genes. The problem with these techniques relies in the redundancy of resulting information, that in most cases generate lots of trivial results with high risk to mask the reality of key biological events. We present and describe a computational method, called GeneTerm Linker, that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. The algorithm is tested with a small set of well known interacting proteins from yeast and with a large collection of reference sets from three heterogeneous resources: multiprotein complexes (CORUM), cellular pathways (SGD) and human diseases (OMIM). Statistical Precision, Recall and balanced F-score are calculated showing robust results, even when different levels of random noise are included in the test sets. Although we could not find an equivalent method, we present a comparative analysis with a widely used method that combines enrichment and functional annotation clustering. A web application to use the method here proposed is provided at http://gtlinker.cnb.csic.es.

Indexed as

AlgorithmsCluster AnalysisComputational BiologyDatabases, GeneticGene Regulatory NetworksGenetic Predisposition to DiseaseHumansInternetNuclear ProteinsProteinsReproducibility of ResultsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSignal TransductionNuclear ProteinsProteinsSaccharomyces cerevisiae Proteins

Identifiers

PMID21949701
PMCPMC3174934

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.