Evidence map›Paper›PMID 36318240›Full record

ArticleNucleic acids research2023

GenomicKB: a knowledge graph for the human genome.

Fan Feng, Feitong Tang, Yijia Gao, Dongyu Zhu, Tianjun Li, Shuyuan Yang, Yuan Yao, Yuanhao Huang, Jie Liu

Abstract read
In one paragraph

Article in Nucleic acids research, 2023. 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.

  1. Article
  2. Article
  3. Review
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  5. A Survey on Unifying Large Language Models and Knowledge Graphs for Biomedicine and Healthcare.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. MetagenomicKG: a knowledge graph for metagenomic applications.bioRxiv : the preprint server for biology · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. 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

9 authors.

Fan FengDepartment of Computational Medicine and Bioinformatics, University of Michigan, MI, USA.
Feitong TangElectrical Engineering and Computer Science, University of Michigan, MI, USA.
Yijia GaoElectrical Engineering and Computer Science, University of Michigan, MI, USA.
Dongyu ZhuSchool of Information, University of Michigan, MI, USA.
Tianjun LiElectrical Engineering and Computer Science, University of Michigan, MI, USA.
Shuyuan YangElectrical Engineering and Computer Science, University of Michigan, MI, USA.
Yuan YaoElectrical Engineering and Computer Science, University of Michigan, MI, USA.
Yuanhao HuangDepartment of Computational Medicine and Bioinformatics, University of Michigan, MI, USA.
Jie LiuDepartment of Computational Medicine and Bioinformatics, University of Michigan, MI, USA.ORCID 0000-0002-9504-0587

Funding

Joint analysis of 3D chromatin organization and 1D epigenomeR35HG011279 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LIU, JIE · 2020 to 2024
$2.1M
NHGRI NIH HHS R35 HG011279
6 · The paper itself

Abstract

Genomic Knowledgebase (GenomicKB) is a graph database for researchers to explore and investigate human genome, epigenome, transcriptome, and 4D nucleome with simple and efficient queries. The database uses a knowledge graph to consolidate genomic datasets and annotations from over 30 consortia and portals, including 347 million genomic entities, 1.36 billion relations, and 3.9 billion entity and relation properties. GenomicKB is equipped with a web-based query system (https://gkb.dcmb.med.umich.edu/) which allows users to query the knowledge graph with customized graph patterns and specific constraints on entities and relations. Compared with traditional tabular-structured data stored in separate data portals, GenomicKB emphasizes the relations among genomic entities, intuitively connects isolated data matrices, and supports efficient queries for scientific discoveries. GenomicKB transforms complicated analysis among multiple genomic entities and relations into coding-free queries, and facilitates data-driven genomic discoveries in the future.

Indexed as

Genome, HumanPattern Recognition, AutomatedGenomicsHumansKnowledge Bases

Identifiers

PMID36318240
PMCPMC9825430

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.