Evidence map›Paper›PMID 27148361›Full record

ArticlePPAR research2016

PPARgene: A Database of Experimentally Verified and Computationally Predicted PPAR Target Genes.

Li Fang, Man Zhang, Yanhui Li, Yan Liu, Qinghua Cui, Nanping Wang

Open access · goldAbstract read
In one paragraph

Article in PPAR research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

73 citing papers in PubMed, 118 citations in OpenAlex.

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  16. Perfluorooctanoic acid induces transcriptomic alterations in second trimester human cytotrophoblasts.Toxicological sciences : an official journal of the Society of Toxicology · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. Article

13 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Li FangInstitute of Cardiovascular Sciences, Peking University Health Science Center, Beijing 100191, China.
Man ZhangInstitute of Cardiovascular Sciences, Peking University Health Science Center, Beijing 100191, China.
Yanhui LiInstitute of Cardiovascular Sciences, Peking University Health Science Center, Beijing 100191, China.
Yan LiuInstitute of Cardiovascular Sciences, Peking University Health Science Center, Beijing 100191, China.
Qinghua CuiDepartment of Biomedical Informatics, Peking University Health Science Center, Beijing 100191, China.
Nanping WangInstitute of Cardiovascular Sciences, Peking University Health Science Center, Beijing 100191, China; The Advanced Institute for Medical Sciences, Dalian Medical University, Dalian 116044, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors of the nuclear receptor superfamily. Upon ligand binding, PPARs activate target gene transcription and regulate a variety of important physiological processes such as lipid metabolism, inflammation, and wound healing. Here, we describe the first database of PPAR target genes, PPARgene. Among the 225 experimentally verified PPAR target genes, 83 are for PPARα, 83 are for PPARβ/δ, and 104 are for PPARγ. Detailed information including tissue types, species, and reference PubMed IDs was also provided. In addition, we developed a machine learning method to predict novel PPAR target genes by integrating in silico PPAR-responsive element (PPRE) analysis with high throughput gene expression data. Fivefold cross validation showed that the performance of this prediction method was significantly improved compared to the in silico PPRE analysis method. The prediction tool is also implemented in the PPARgene database.

Identifiers

PMID27148361
PMCPMC4842375
OpenAlexW2333828476

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.