Evidence map›Paper›PMID 25392693›Full record

ArticleCancer informatics2014

Co-expression Network Analysis of Human lncRNAs and Cancer Genes.

Steven B Cogill, Liangjiang Wang

Abstract read
In one paragraph

Article in Cancer informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
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  5. Article
  6. Review
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  8. Review
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  11. Article
  12. Genomic data mining for functional annotation of human long noncoding RNAs.Journal of Zhejiang University. Science. B · 2019
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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  19. Article
  20. LncRNAs and cancer.Oncology letters · 2016
    Article
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

2 authors.

Steven B CogillDepartment of Genetics and Biochemistry, Clemson University, Clemson, SC, USA.
Liangjiang WangDepartment of Genetics and Biochemistry, Clemson University, Clemson, SC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We used gene co-expression network analysis to functionally annotate long noncoding RNAs (lncRNAs) and identify their potential cancer associations. The integrated microarray data set from our previous study was used to extract the expression profiles of 1,865 lncRNAs. Known cancer genes were compiled from the Catalogue of Somatic Mutations in Cancer and UniProt databases. Co-expression analysis identified a list of previously uncharacterized lncRNAs that showed significant correlation in expression with core cancer genes. To further annotate the lncRNAs, we performed a weighted gene co-expression network analysis, which resulted in 37 co-expression modules. Three biologically interesting modules were analyzed in depth. Two of the modules showed relatively high expression in blood and brain tissues, whereas the third module was found to be downregulated in blood cells. Hub lncRNA genes and enriched functional annotation terms were identified within the modules. The results suggest the utility of this approach as well as potential roles of uncharacterized lncRNAs in leukemia and neuroblastoma.

Indexed as

cancerco-expressionlncRNAmicroarraynetwork analysis

Identifiers

PMID25392693
PMCPMC4218681

What OpenQuestion holds

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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.