Evidence map›Paper›PMID 28690910›Full record

ArticleNational science review2016

Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data.

Yong Wang, Rui Jiang, Wing Hung Wong

Open access · hybridAbstract read
In one paragraph

Article in National science review, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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

3 authors at 1 institution in 2 countries.

Yong WangDepartment of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305, USA.
Rui JiangDepartment of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305, USA.
Wing Hung WongDepartment of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305, USA.
Stanford University · US

Funding

Special EquipmentP50HG007735 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2014 to 2018
$15.2M
Statistical and computational analysis in whole genome sequencing studies.R01HG007834 · NHGRI · STANFORD UNIVERSITY · PI WONG, WING H. · 2014 to 2016
$892k
NHGRI NIH HHS P50 HG007735NHGRI NIH HHS R01 HG007834
6 · The paper itself

Abstract

Cell packs a lot of genetic and regulatory information through a structure known as chromatin, i.e. DNA is wrapped around histone proteins and is tightly packed in a remarkable way. To express a gene in a specific coding region, the chromatin would open up and DNA loop may be formed by interacting enhancers and promoters. Furthermore, the mediator and cohesion complexes, sequence-specific transcription factors, and RNA polymerase II are recruited and work together to elaborately regulate the expression level. It is in pressing need to understand how the information, about when, where, and to what degree genes should be expressed, is embedded into chromatin structure and gene regulatory elements. Thanks to large consortia such as Encyclopedia of DNA Elements (ENCODE) and Roadmap Epigenomic projects, extensive data on chromatin accessibility and transcript abundance are available across many tissues and cell types. This rich data offer an exciting opportunity to model the causal regulatory relationship. Here, we will review the current experimental approaches, foundational data, computational problems, interpretive frameworks, and integrative models that will enable the accurate interpretation of regulatory landscape. Particularly, we will discuss the efforts to organize, analyze, model, and integrate the DNA accessibility data, transcriptional data, and functional genomic regions together. We believe that these efforts will eventually help us understand the information flow within the cell and will influence research directions across many fields.

Indexed as

data integrationDNA accessibilitygene regulatory networkopen chromatinstatistical modeltranscription factor colocalization

Identifiers

PMID28690910
PMCPMC5501464
OpenAlexW2342138444

What OpenQuestion holds

Textmetadata
LicenceTDM
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.