Evidence map›Paper›PMID 40866611›Full record

ArticleCommunications biology2025

Deciphering chromatin domain, domain community and chromunity for 3D genome maps with Mactop.

Ran Duan, Dachang Dang, Shichen Fan, Shaowen Yao, Shihua Zhang

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Ran DuanDepartment of Communications Engineering, College of Information, Yunnan University, Kunming, 650091, China.ORCID http://orcid.org/0009-0004-4581-2317
Dachang DangKey Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China.ORCID http://orcid.org/0000-0002-0184-6265
Shichen FanSchool of Computer Science and Technology, Xidian University, Xi'an, 710071, China.
Shaowen YaoDepartment of Software Engineering, Yunnan University, Kunming, 650500, China. yaosw@ynu.edu.cn.ORCID http://orcid.org/0000-0003-1516-4246
Shihua ZhangNCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 100190, Beijing, China. zsh@amss.ac.cn.ORCID http://orcid.org/0000-0003-0192-7118

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced high-throughput chromosome conformation capture techniques, like Hi-C, reveal genome organization into structural units like topologically associating domains (TADs), which are crucial in gene expression regulation. While accurately identifying TADs is vital, distinguishing different types of TAD boundaries and TAD categories remains a significant challenge in genomic research. We develop a Markov clustering-based tool, Mactop, to accurately identify TADs and provide biologically important classifications of TADs and their boundaries. Mactop distinguishes stable and dynamic boundaries based on biological significance. Mactop shows superior performance against multiple TAD-calling methods. More importantly, leveraging spatial interactions among TADs, Mactop uncovers TAD communities characterized by chromatin accessibility and enriched histone modifications. Mactop unveils the 'chromunity' within TADs in high-order interaction data, showing that interactions within TADs are diverse rather than uniform. In short, Mactop is a versatile, accurate, robust tool for deciphering chromatin domain, domain community, and chromunity for 3D genome maps.

Indexed as

ChromatinChromosome MappingSoftwareGenomicsHumansMarkov ChainsChromatin

Identifiers

PMID40866611
PMCPMC12391324

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.