Evidence map›Paper›PMID 27899673›Full record

ReviewNucleic acids research2017

DiseaseMeth version 2.0: a major expansion and update of the human disease methylation database.

Yichun Xiong, Yanjun Wei, Yue Gu, Shumei Zhang, Jie Lyu, Bin Zhang, Chuangeng Chen, Jiang Zhu, Yihan Wang, Hongbo Liu and 1 more

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed, 1 pooled it
5.2field-weighted citation impact, top 4% of its field
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

103 citing papers in PubMed, 1 synthesis or guideline pooled it, 164 citations in OpenAlex.

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  10. miR-335-5p Inhibits EMT and PI3K/AKT Pathways via MARCH8.Indian journal of clinical biochemistry : IJCB · 2025
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43 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

11 authors at 2 institutions in 2 countries.

Yichun XiongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yanjun WeiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yue GuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Shumei ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Jie LyuDan L. Duncan Cancer Center, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.
Bin ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Chuangeng ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Jiang ZhuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yihan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Hongbo LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China hongbo919@gmail.com.
Yan ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China tyozhang@ems.hrbmu.edu.cn.
Harbin Medical University · CNBaylor College of Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease-gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease-gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease-disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.

Indexed as

Databases, GeneticDNA MethylationSearch EngineComputational BiologyEpigenomicsGene Expression ProfilingGenetic Association StudiesHumansSoftwareWeb Browser

Identifiers

PMID27899673
PMCPMC5210584
OpenAlexW2557962097

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.