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Attention Score in Context
| Title |
Combining membrane proteomics and computational three-way pathway analysis revealed signalling pathways preferentially regulated in human iPSCs and human ESCs
|
|---|---|
| Published in |
Scientific Reports, November 2017
|
| DOI | 10.1038/s41598-017-15347-z |
| Pubmed ID | |
| Authors |
Wei-Sheng Tien, Pei-Mien Chen, Ching-Yu Chuang, Shook-Mun Lui, Hung-Chih Kuo, Yu-Ju Chen, Kun-Pin Wu |
| Abstract |
Owing to the clinical potential of human induced pluripotent stem cells (hiPSCs) in regenerative medicine, a thorough examination of the similarities and differences between hiPSCs and human embryonic stem cells (hESCs) has become indispensable. Moreover, as the important roles of membrane proteins in biological signalling, functional analyses of membrane proteome are therefore promising. In this study, a pathway analysis by the bioinformatics tool GSEA was first performed to identify significant pathways associated with the three comparative membrane proteomics experiments: hiPSCs versus precursor human foreskin fibroblasts (HFF), hESCs versus precursor HFF, and hiPSCs versus hESCs. A following three-way pathway comparison was conducted to identify the differentially regulated pathways that may contribute to the differences between hiPSCs and hESCs. Our results revealed that pathways related to oxidative phosphorylation and focal adhesion may undergo incomplete regulations during the reprogramming process. This hypothesis was supported by another public proteomics dataset to a certain degree. The identified pathways and their core enriched proteins could serve as the starting point to explore the possible ways to make hiPSCs closer to hESCs. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
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 > Bachelor | 6 | 27% |
| Researcher | 5 | 23% |
| Student > Master | 3 | 14% |
| Student > Ph. D. Student | 2 | 9% |
| Professor > Associate Professor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 36% |
| Agricultural and Biological Sciences | 3 | 14% |
| Engineering | 2 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Environmental Science | 1 | 5% |
| Other | 4 | 18% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 12 November 2017.
All research outputs
#3,665,870
of 23,007,887 outputs
Outputs from Scientific Reports
#29,461
of 124,268 outputs
Outputs of similar age
#68,177
of 331,430 outputs
Outputs of similar age from Scientific Reports
#960
of 4,445 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 124,268 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,430 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 4,445 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.