Evidence map›Paper›PMID 17932060›Full record

ArticleNucleic acids research2008

PubMeth: a cancer methylation database combining text-mining and expert annotation.

Maté Ongenaert, Leander Van Neste, Tim De Meyer, Gerben Menschaert, Sofie Bekaert, Wim Van Criekinge

Abstract read
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 1 pooled it
–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

85 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Databases and prospects of dynamic gene regulation in eukaryotes: A mini review.Computational and structural biotechnology journal · 2023
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. ILDgenDB: integrated genetic knowledge resource for interstitial lung diseases (ILDs).Database : the journal of biological databases and curation · 2018
    Article
  18. Article
  19. Article
  20. AAgAtlas 1.0: a human autoantigen database.Nucleic acids research · 2017
    Article

25 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.

Maté OngenaertDepartment of Molecular Biotechnology, Faculty of Bioscience Engineering, Laboratory for Bioinformatics and Computational Genomics, Ghent University, B-9000 Ghent, Belgium. mate.ongenaert@ugent.be
Leander Van Neste
Tim De Meyer
Gerben Menschaert
Sofie Bekaert
Wim Van Criekinge

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http://www.pubmeth.org. PubMeth is based on text-mining of Medline/PubMed abstracts, combined with manual reading and annotation of preselected abstracts. The text-mining approach results in increased speed and selectivity (as for instance many different aliases of a gene are searched at once), while the manual screening significantly raises the specificity and quality of the database. The summarized overview of the results is very useful in case more genes or cancer types are searched at the same time.

Indexed as

Databases, GeneticDNA MethylationGenes, NeoplasmInternetMEDLINENeoplasmsPubMedUser-Computer Interface

Identifiers

PMID17932060
PMCPMC2238841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.