SyStemCell: a database populated with multiple levels of experimental data from stem cell differentiation research.
Elucidation of the mechanisms of stem cell differentiation is of great scientific interest. Increasing evidence suggests that stem cell differentiation involves changes at multiple levels of biological regulation, which together orchestrate the complex differentiation process; many related studies have been performed to investigate the various levels of regulation. The resulting valuable data, however, remain scattered. Most of the current stem cell-relevant databases focus on a single level of regulation (mRNA expression) from limited stem cell types; thus, a unifying resource would be of great value to compile the multiple levels of research data available. Here we present a database for this purpose, SyStemCell, deposited with multi-level experimental data from stem cell research. The database currently covers seven levels of stem cell differentiation-associated regulatory mechanisms, including DNA CpG 5-hydroxymethylcytosine/methylation, histone modification, transcript products, microRNA-based regulation, protein products, phosphorylation proteins and transcription factor regulation, all of which have been curated from 285 peer-reviewed publications selected from PubMed. The database contains 43,434 genes, recorded as 942,221 gene entries, for four organisms (Homo sapiens, Mus musculus, Rattus norvegicus, and Macaca mulatta) and various stem cell sources (e.g., embryonic stem cells, neural stem cells and induced pluripotent stem cells). Data in SyStemCell can be queried by Entrez gene ID, symbol, alias, or browsed by specific stem cell type at each level of genetic regulation. An online analysis tool is integrated to assist researchers to mine potential relationships among different regulations, and the potential usage of the database is demonstrated by three case studies. SyStemCell is the first database to bridge multi-level experimental information of stem cell studies, which can become an important reference resource for stem cell researchers. The database is available at http://lifecenter.sgst.cn/SyStemCell/.
Shanghai Center for Bioinformation Technology, Shanghai, China.
Jian
J
Yu
Xiaobin
X
Xing
Lingyao
L
Zeng
Jiehuan
J
Sun
Wei
W
Li
Han
H
Sun
Ying
Y
He
Jing
J
Li
Guoqing
G
Zhang
Chuan
C
Wang
Yixue
Y
Li
Lu
L
Xie
D000818:Animals; D002454:Cell Differentiation; D019175:DNA Methylation; D016208:Databases, Factual; D030541:Databases, Genetic; D053595:Embryonic Stem Cells / Q000378:metabolism*; D005786:Gene Expression Regulation; D006657:Histones / Q000235:genetics; D006801:Humans; D057026:Induced Pluripotent Stem Cells / Q000378:metabolism*; D020407:Internet; D008253:Macaca mulatta / Q000235:genetics*; D051379:Mice; D035683:MicroRNAs / Q000235:genetics; D058953:Neural Stem Cells / Q000378:metabolism*; D010766:Phosphorylation; D012333:RNA, Messenger / Q000235:genetics; D051381:Rats; D012984:Software; D014157:Transcription Factors / Q000235:genetics
D006657:Histones; D035683:MicroRNAs; D012333:RNA, Messenger; D014157:Transcription Factors