| Title |
A computationally constructed ceRNA interaction network based on a comparison of the SHEE and SHEEC cell lines
|
|---|---|
| Published in |
Cellular & Molecular Biology Letters, September 2016
|
| DOI | 10.1186/s11658-016-0022-0 |
| Pubmed ID | |
| Authors |
Jiachun Sun, Junqiang Yan, Xiaozhi Yuan, Ruina Yang, Tanyou Dan, Xinshuai Wang, Guoqiang Kong, Shegan Gao |
| Abstract |
Long non-coding RNAs (lncRNAs) play critical and complicated roles in the regulation of various biological processes, including chromatin modification, transcription and post-transcriptional processing. Interestingly, some lncRNAs serve as miRNA "sponges" that inhibit interaction with miRNA targets in post-transcriptional regulation. We constructed a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression based on high-throughput RNA sequencing and microarray data to enable a comparison of the SHEE and SHEEC cell lines. Using Targetscan and miRanda bioinformatics algorithms and miRTarbase microRNA-target interactions database, we established that 51 miRNAs sharing 13,623 MREs with 2260 genes and 82 lncRNAs were involved in this ceRNA network. Through a biological function analysis, the ceRNA network appeared to be primarily involved in cell proliferation, apoptosis, the cell cycle, invasion and metastasis. Functional pathway analyses demonstrated that the ceRNA network potentially modulated multiple signaling pathways, such as the MAPK, Ras, HIF-1, Rap1, and PI3K/Akt signaling pathways. These results might provide new clues to better understand the regulation of the ceRNA network in cancer. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 50% |
| France | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Other | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 9 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 23% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Immunology and Microbiology | 2 | 9% |
| Computer Science | 1 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 8 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 July 2017.
All research outputs
#15,462,982
of 22,977,819 outputs
Outputs from Cellular & Molecular Biology Letters
#160
of 482 outputs
Outputs of similar age
#205,077
of 323,220 outputs
Outputs of similar age from Cellular & Molecular Biology Letters
#3
of 9 outputs
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