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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Study of cell differentiation by phylogenetic analysis using histone modification data
|
|---|---|
| Published in |
BMC Bioinformatics, August 2014
|
| DOI | 10.1186/1471-2105-15-269 |
| Pubmed ID | |
| Authors |
Nishanth Ulhas Nair, Yu Lin, Ana Manasovska, Jelena Antic, Paulina Grnarova, Avinash Das Sahu, Philipp Bucher, Bernard ME Moret |
| Abstract |
In cell differentiation, a cell of a less specialized type becomes one of a more specialized type, even though all cells have the same genome. Transcription factors and epigenetic marks like histone modifications can play a significant role in the differentiation process. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 14% |
| France | 1 | 14% |
| Norway | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 2% |
| Finland | 1 | 2% |
| United States | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 40 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 30% |
| Student > Master | 9 | 20% |
| Student > Bachelor | 6 | 14% |
| Researcher | 6 | 14% |
| Professor | 3 | 7% |
| Other | 5 | 11% |
| Unknown | 2 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 36% |
| Biochemistry, Genetics and Molecular Biology | 12 | 27% |
| Computer Science | 7 | 16% |
| Chemistry | 3 | 7% |
| Mathematics | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 1 | 2% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 13 October 2014.
All research outputs
#7,134,371
of 22,759,618 outputs
Outputs from BMC Bioinformatics
#2,830
of 7,273 outputs
Outputs of similar age
#69,679
of 230,503 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 122 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 60% 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 230,503 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 122 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.