Evidence map›Paper›PMID 35251128›Full record

ArticleFrontiers in genetics2022

Integration of Count Difference and Curve Similarity in Negative Regulatory Element Detection.

Na He, Wenjing Wang, Chao Fang, Yongjian Tan, Li Li, Chunhui Hou

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2022. 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
1.0field-weighted citation impact, top 26% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  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

6 authors at 5 institutions in 2 countries.

Na HeHarbin Institute of Technology, Harbin, China.
Wenjing WangSchool of Life Science and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Chao FangCancer Centre, Faculty of Health Sciences, University of Macau, Macao, China.
Yongjian TanDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
Li LiDepartment of Bioinformatics, Huazhong Agricultural University, Wuhan, China.
Chunhui HouDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
Southern University of Science and Technology · CNChinese University of Hong Kong · CNHarbin Institute of Technology · CNHuazhong Agricultural University · CNUniversity of Macau · MO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Negative regulatory elements (NREs) down-regulate gene expression by inhibiting the activities of promoters or enhancers. The repressing activity of NREs can be measured globally by massively parallel reporter assays (MPRAs). However, most existing algorithms are designed for the statistical detection of positively enriched signals in MPRA datasets. To identify reduced signals in MPRA experiments, we designed a NRE identification program, fast-NR, by integrating the count and graphic features of sequenced reads to detect NREs using datasets generated by experiments of self-transcribing active regulatory region sequencing (STARR-seq). Fast-NR identified hundreds of silencers in human K562 cells that can be validated by independent methods.

Indexed as

count differencecurve similaritynegative regulatory elementsilencersilencer identification

Identifiers

PMID35251128
PMCPMC8896116
OpenAlexW4213305032

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.