Evidence map›Paper›PMID 30871473›Full record

ArticleBMC genomics2019

TADKB: Family classification and a knowledge base of topologically associating domains.

Tong Liu, Jacob Porter, Chenguang Zhao, Hao Zhu, Nan Wang, Zheng Sun, Yin-Yuan Mo, Zheng Wang

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
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  5. Interplay Between 3D Chromatin Architecture and Gene Regulation at theInternational journal of molecular sciences · 2025
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  11. Learning Micro-C from Hi-C with diffusion models.PLoS computational biology · 2024
    Article
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  18. Technologies, strategies, and cautions when deconvoluting genome-wide association signals: FTO in focus.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2023
    Review
  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

8 authors.

Tong LiuDepartment of Computer Science, University of Miami, 1365 Memorial Drive, Coral Gables, FL, 33124-4245, USA.
Jacob PorterSchool of Computing Sciences and Computer Engineering, University of Southern Mississippi, 118 College Drive, Hattiesburg, MS, 39406, USA.
Chenguang ZhaoSchool of Computing Sciences and Computer Engineering, University of Southern Mississippi, 118 College Drive, Hattiesburg, MS, 39406, USA.
Hao ZhuSchool of Computing Sciences and Computer Engineering, University of Southern Mississippi, 118 College Drive, Hattiesburg, MS, 39406, USA.
Nan WangDepartment of Computer Science, New Jersey City University, 2039 Kennedy Blvd, Jersey City, NJ, 07305, USA.
Zheng SunDepartment of Electrical and Computer Engineering, California Baptist University, 3739 Adams Street, Riverside, CA, 92504, USA.
Yin-Yuan MoDepartment of Pharmacology and Toxicology, University of Mississippi Medical Center, 2500 N State St, Jackson, MS, 39216, USA.
Zheng WangDepartment of Computer Science, University of Miami, 1365 Memorial Drive, Coral Gables, FL, 33124-4245, USA. zheng.wang@miami.edu.

Funding

Measure and Classify the Structure and Function of Genome Topological DomainsR15GM120650 · NIGMS · UNIVERSITY OF SOUTHERN MISSISSIPPI · PI SUNG, ANDREW H. · 2016 to 2016
$444k
National Institute of General Medical Sciences (US) R15GM120650NIGMS NIH HHS R15 GM120650
6 · The paper itself

Abstract

backgroundTopologically associating domains (TADs) are considered the structural and functional units of the genome. However, there is a lack of an integrated resource for TADs in the literature where researchers can obtain family classifications and detailed information about TADs.

resultsWe built an online knowledge base TADKB integrating knowledge for TADs in eleven cell types of human and mouse. For each TAD, TADKB provides the predicted three-dimensional (3D) structures of chromosomes and TADs, and detailed annotations about the protein-coding genes and long non-coding RNAs (lncRNAs) existent in each TAD. Besides the 3D chromosomal structures inferred by population Hi-C, the single-cell haplotype-resolved chromosomal 3D structures of 17 GM12878 cells are also integrated in TADKB. A user can submit query gene/lncRNA ID/sequence to search for the TAD(s) that contain(s) the query gene or lncRNA. We also classified TADs into families. To achieve that, we used the TM-scores between reconstructed 3D structures of TADs as structural similarities and the Pearson's correlation coefficients between the fold enrichment of chromatin states as functional similarities. All of the TADs in one cell type were clustered based on structural and functional similarities respectively using the spectral clustering algorithm with various predefined numbers of clusters. We have compared the overlapping TADs from structural and functional clusters and found that most of the TADs in the functional clusters with depleted chromatin states are clustered into one or two structural clusters. This novel finding indicates a connection between the 3D structures of TADs and their DNA functions in terms of chromatin states.

conclusionTADKB is available at http://dna.cs.miami.edu/TADKB/ .

Indexed as

Chromatin Assembly and DisassemblyChromosomes, MammalianGene Expression RegulationGenomeKnowledge BasesAlgorithmsAnimalsGenomicsHumansMiceMultigene FamilyRNA, Long NoncodingRNA, Long NoncodingFamily classificationlncRNAsLong non-coding RNAsSingle-cell 3D genome structuresTADsTopologically associating domains

Identifiers

PMID30871473
PMCPMC6419456

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LicenceCC BY
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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.