Evidence map›Paper›PMID 29161430›Full record

ArticleNucleic acids research2018

MethBank 3.0: a database of DNA methylomes across a variety of species.

Rujiao Li, Fang Liang, Mengwei Li, Dong Zou, Shixiang Sun, Yongbing Zhao, Wenming Zhao, Yiming Bao, Jingfa Xiao, Zhang Zhang

Abstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

  1. Article
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  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Databases and prospects of dynamic gene regulation in eukaryotes: A mini review.Computational and structural biotechnology journal · 2023
    Review
  11. Epigenetic modifications: Allusive clues of lncRNA functions in plants.Computational and structural biotechnology journal · 2023
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Genome Warehouse: A Public Repository Housing Genome-scale Data.Genomics, proteomics & bioinformatics · 2021
    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

10 authors.

Rujiao LiBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Fang LiangBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Mengwei LiBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Dong ZouBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Shixiang SunBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Yongbing ZhaoLymphocyte Nuclear Biology, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
Wenming ZhaoBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Yiming BaoBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Jingfa XiaoBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Zhang ZhangBIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MethBank (http://bigd.big.ac.cn/methbank) is a database that integrates high-quality DNA methylomes across a variety of species and provides an interactive browser for visualization of methylation data. Here, we present an updated implementation of MethBank (version 3.0) by incorporating more DNA methylomes from multiple species and equipping with more enhanced functionalities for data annotation and more friendly web interfaces for data presentation, search and visualization. MethBank 3.0 features large-scale integration of high-quality methylomes, involving 34 consensus reference methylomes derived from a large number of human samples, 336 single-base resolution methylomes from different developmental stages and/or tissues of five plants, and 18 single-base resolution methylomes from gametes and early embryos at multiple stages of two animals. Additionally, it is enhanced by improving the functionalities for data annotation, which accordingly enables systematic identification of methylation sites closely associated with age, sites with constant methylation levels across different ages, differentially methylated promoters, age-specific differentially methylated cytosines/regions, and methylated CpG islands. Moreover, MethBank provides tools to estimate human methylation age online and to identify differentially methylated promoters, respectively. Taken together, MethBank is upgraded with significant improvements and advances over the previous version, which is of great help for deciphering DNA methylation regulatory mechanisms for epigenetic studies.

Indexed as

Databases, GeneticDNA MethylationAnimalsCpG IslandsCytosineHumansMicePromoter Regions, GeneticWhole Genome SequencingCytosine

Identifiers

PMID29161430
PMCPMC5753180

What OpenQuestion holds

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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.