Evidence map›Paper›PMID 26694485›Full record

ArticleGenome biology2015

3CPET: finding co-factor complexes from ChIA-PET data using a hierarchical Dirichlet process.

Mohamed Nadhir Djekidel, Zhengyu Liang, Qi Wang, Zhirui Hu, Guipeng Li, Yang Chen, Michael Q Zhang

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

17 citing papers in PubMed, 25 citations in OpenAlex.

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  14. Modeling gene regulation from paired expression and chromatin accessibility data.Proceedings of the National Academy of Sciences of the United States of America · 2017
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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

7 authors at 4 institutions in 4 countries.

Mohamed Nadhir DjekidelMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. nde12@mails.tsinghua.edu.cn.
Zhengyu LiangMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. liangzy12@mails.tsinghua.edu.cn.
Qi WangMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. wqwq_945@163.com.
Zhirui HuMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. xyz111131@gmail.com.
Guipeng LiMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. ligp12@mails.tsinghua.edu.cn.
Yang ChenMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. yc@tsinghua.edu.cn.
Michael Q ZhangMOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. michaelzhang@tsinghua.edu.cn.
Institute of Bioinformatics · INInstitut de Biologie systémique et synthétique · FRCenter for Systems Biology · USTsinghua University · CN

Funding

Selectively targeting delta opioid receptor subtypes to control drinking behaviorR01AA020401 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WHISTLER, JENNIFER L · 2011 to 2015
$1.8M
NIAAA NIH HHS R01 AA020401
6 · The paper itself

Abstract

Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies. 3CPET does so by combining data from ChIA-PET, transcription factor binding sites, and protein interactions. 3CPET results show biologically significant and accurate predictions when validated against experimental and simulation data.

Indexed as

AlgorithmsChromatinHumansMCF-7 CellsProtein BindingTranscription FactorsChromatinTranscription Factors

Identifiers

PMID26694485
PMCPMC4716632
OpenAlexW2215072981

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.