Evidence map›Paper›PMID 34792145›Full record

ArticleNucleic acids research2022

DiseaseMeth version 3.0: a major expansion and update of the human disease methylation database.

Jie Xing, Ruiyang Zhai, Cong Wang, Honghao Liu, Jiaqi Zeng, Dianshuang Zhou, Mengyan Zhang, Liru Wang, Qiong Wu, Yue Gu and 1 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  18. Databases and prospects of dynamic gene regulation in eukaryotes: A mini review.Computational and structural biotechnology journal · 2023
    Review
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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

11 authors.

Jie XingSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Ruiyang ZhaiSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Cong WangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Honghao LiuSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Jiaqi ZengSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Dianshuang ZhouSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Mengyan ZhangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Liru WangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Qiong WuSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Yue GuSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Yan ZhangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0002-5307-2484

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation has a growing potential for use as a biomarker because of its involvement in disease. DNA methylation data have also substantially grown in volume during the past 5 years. To facilitate access to these fragmented data, we proposed DiseaseMeth version 3.0 based on DiseaseMeth version 2.0, in which the number of diseases including increased from 88 to 162 and High-throughput profiles samples increased from 32 701 to 49 949. Experimentally confirmed associations added 448 pairs obtained by manual literature mining from 1472 papers in PubMed. The search, analyze and tools sections were updated to increase performance. In particular, the FunctionSearch now provides for the functional enrichment of genes from localized GO and KEGG annotation. We have also developed a unified analysis pipeline for identifying differentially DNA methylated genes (DMGs) from the original data stored in the database. 22 718 DMGs were found in 99 diseases. These DMGs offer application in disease evaluation using two self-developed online tools, Methylation Disease Correlation and Cancer Prognosis & Co-Methylation. All query results can be downloaded and can also be displayed through a box plot, heatmap or network module according to whichever search section is used. DiseaseMeth version 3.0 is freely available at http://diseasemeth.edbc.org/.

Indexed as

Databases, FactualBiomarkers, TumorDNA MethylationGene Expression ProfilingGenetic Diseases, InbornHumansNeoplasmsPubMedBiomarkers, Tumor

Identifiers

PMID34792145
PMCPMC8728278

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.