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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Posttranscriptional (Re)programming of Cell Fate: Examples in Stem Cells, Progenitor, and Differentiated Cells
|
|---|---|
| Published in |
Frontiers in immunology, April 2018
|
| DOI | 10.3389/fimmu.2018.00715 |
| Pubmed ID | |
| Authors |
Chrysi Kanellopoulou, Stefan A. Muljo |
| Abstract |
How a single genome can give rise to many different transcriptomes and thus all the different cell lineages in the human body is a fundamental question in biology. While signaling pathways, transcription factors, and chromatin architecture, to name a few determinants, have been established to play critical roles, recently, there is a growing appreciation of the roles of non-coding RNAs and RNA-binding proteins in controlling cell fates posttranscriptionally. Thus, it is vital that these emerging players are also integrated into models of gene regulatory networks that underlie programs of cellular differentiation. Sometimes, we can leverage knowledge about such posttranscriptional circuits to reprogram patterns of gene expression in meaningful ways. Here, we review three examples from our work. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Singapore | 1 | 25% |
| Switzerland | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 31% |
| Student > Postgraduate | 3 | 19% |
| Researcher | 3 | 19% |
| Professor | 2 | 13% |
| Student > Doctoral Student | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 63% |
| Agricultural and Biological Sciences | 1 | 6% |
| Immunology and Microbiology | 1 | 6% |
| Psychology | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 2 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 16 May 2018.
All research outputs
#15,175,718
of 25,382,440 outputs
Outputs from Frontiers in immunology
#14,217
of 31,537 outputs
Outputs of similar age
#182,008
of 343,375 outputs
Outputs of similar age from Frontiers in immunology
#398
of 692 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,537 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 52% 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 343,375 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 692 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.