Applying Differentially Expressed Genes From Rodent Models of Chronic Stress to Research of Stress-Related Disease: An Online Database
Applying Differentially Expressed Genes From Rodent Models of Chronic Stress to Research of Stress-Related Disease: An Online Database
复制标题
将慢性应激啮齿动物模型的差异表达基因应用于应激相关疾病的研究:在线数据库
DOI:
10.1097/psy.0000000000000102
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发表时间:
2014-10
影响因子:
3.3
通讯作者:
Wang, Jing
中科院分区:
文献类型:
--
作者:
Du, Yang;Chang, Suhua;Zhang, Weina;Wang, Jing
Objective To systematically collect differentially expressed genes (DEGs) from rodent models of chronic stress (CS) and apply them to research of stress-related disease. CS is an important environmental factor that may affect numerous complex diseases. Its relevant DEGs identified from rodent models provide valuable information for understanding the mechanisms underlying stress-related diseases. Currently, no suitable data tool have been developed to use such data. Methods We systematically searched and reviewed publications in PubMed. CS-DEGs were collected from original studies that reported gene expression statuses in rodent models of CS. CS disease overlapping genes, CS pathways and CS pathway clusters, and CS regulatory elements were analyzed on the basis of CS-DEGs. An online database was developed to store and manage curated CS-DEGs and analyzed data. Results A total of 2956 CS-DEGs were collected from 195 articles, among which 815 genes are shared among CS and seven stress-related diseases. Nine hundred twenty-seven CS pathway clusters were identified. Three types of CS regulatory elements are predicted for all CS genes. An online database (CS-DEGs), freely available at http://cs.psych.ac.cn, includes and presents CS-DEGs and all analyzed data. Conclusions CS-DEGs is the first gene database on CS research. It enables researchers to apply rodent expression data in candidate gene and pathway identification for stress-related disease study.
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影响因子:
14.9
作者:
Ye H;Liu X;Lv M;Wu Y;Kuang S;Gong J;Yuan P;Zhong Z;Li Q;Jia H;Sun J;Chen Z;Guo AY
通讯作者:
Guo AY
影响因子:
14.9
作者:
Flicek P;Amode MR;Barrell D;Beal K;Billis K;Brent S;Carvalho-Silva D;Clapham P;Coates G;Fitzgerald S;Gil L;Girón CG;Gordon L;Hourlier T;Hunt S;Johnson N;Juettemann T;Kähäri AK;Keenan S;Kulesha E;Martin FJ;Maurel T;McLaren WM;Murphy DN;Nag R;Overduin B;Pignatelli M;Pritchard B;Pritchard E;Riat HS;Ruffier M;Sheppard D;Taylor K;Thormann A;Trevanion SJ;Vullo A;Wilder SP;Wilson M;Zadissa A;Aken BL;Birney E;Cunningham F;Harrow J;Herrero J;Hubbard TJ;Kinsella R;Muffato M;Parker A;Spudich G;Yates A;Zerbino DR;Searle SM
通讯作者:
Searle SM
影响因子:
14.9
作者:
D'Antonio M;Pendino V;Sinha S;Ciccarelli FD
通讯作者:
Ciccarelli FD
影响因子:
9.9
作者:
J. Kelly;C. Filley
通讯作者:
C. Filley
影响因子:
37.3
作者:
Arranz A;Venihaki M;Mol B;Androulidaki A;Dermitzaki E;Rassouli O;Ripoll J;Stathopoulos EN;Gomariz RP;Margioris AN;Tsatsanis C
通讯作者:
Tsatsanis C