Evidence map›Paper›PMID 35600920›Full record

ArticleSTAR protocols2022

3DCoop: An approach for computational inference of cell-type-specific transcriptional regulators cooperation in 3D chromatin.

Xianfu Yi, Menghan Luo, Xiangling Feng, Yao Zhou, Jianhua Wang, Mulin Jun Li

Abstract read
In one paragraph

Article in STAR protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Xianfu YiDepartment of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
Menghan LuoDepartment of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
Xiangling FengDepartment of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
Yao ZhouDepartment of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
Jianhua WangDepartment of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.
Mulin Jun LiDepartment of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precise identification of context-specific transcriptional regulators (TRs) cooperation facilitates the understanding of complex gene regulation. However, previous methods are highly reliant on the availability of ChIPped TRs. Here, we provide a protocol for running 3DCoop, a pipeline for computational inference of cell type-specific TR cooperation in 3D chromatin by integrating TR motifs, open chromatin profiles, gene expression, and chromatin loops. 3DCoop provides a feasible solution to study the potential interplay among TRs across multiple human or mouse tissue/cell types. For complete details on the use and execution of this protocol, please refer to Yi et al. (2021).

Indexed as

ChromatinTranscription FactorsAnimalsGene Expression RegulationHumansMiceChromatinTranscription FactorsBioinformaticsGene ExpressionGeneticsGenomicsSystems biology

Identifiers

PMID35600920
PMCPMC9114683

What OpenQuestion holds

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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.