PPARgene: A Database of Experimentally Verified and Computationally Predicted PPAR Target Genes
Joint Authors
Fang, Li
Zhang, Man
Li, Yanhui
Liu, Yan
Wang, Nanping
Cui, Q.
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-11
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Fang, Li& Zhang, Man& Li, Yanhui& Liu, Yan& Cui, Q.& Wang, Nanping. 2016. PPARgene: A Database of Experimentally Verified and Computationally Predicted PPAR Target Genes. PPAR Research،Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1115331
Modern Language Association (MLA)
Fang, Li…[et al.]. PPARgene: A Database of Experimentally Verified and Computationally Predicted PPAR Target Genes. PPAR Research No. 2016 (2016), pp.1-6.
https://search.emarefa.net/detail/BIM-1115331
American Medical Association (AMA)
Fang, Li& Zhang, Man& Li, Yanhui& Liu, Yan& Cui, Q.& Wang, Nanping. PPARgene: A Database of Experimentally Verified and Computationally Predicted PPAR Target Genes. PPAR Research. 2016. Vol. 2016, no. 2016, pp.1-6.
https://search.emarefa.net/detail/BIM-1115331
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1115331