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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Plus ça change – evolutionary sequence divergence predicts protein subcellular localization signals
|
|---|---|
| Published in |
BMC Genomics, January 2014
|
| DOI | 10.1186/1471-2164-15-46 |
| Pubmed ID | |
| Authors |
Yoshinori Fukasawa, Ross KK Leung, Stephen KW Tsui, Paul Horton |
| Abstract |
Protein subcellular localization is a central problem in understanding cell biology and has been the focus of intense research. In order to predict localization from amino acid sequence a myriad of features have been tried: including amino acid composition, sequence similarity, the presence of certain motifs or domains, and many others. Surprisingly, sequence conservation of sorting motifs has not yet been employed, despite its extensive use for tasks such as the prediction of transcription factor binding sites. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Netherlands | 1 | 4% |
| Unknown | 21 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 43% |
| Researcher | 5 | 22% |
| Student > Bachelor | 2 | 9% |
| Student > Master | 2 | 9% |
| Librarian | 1 | 4% |
| Other | 3 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 61% |
| Biochemistry, Genetics and Molecular Biology | 5 | 22% |
| Computer Science | 2 | 9% |
| Medicine and Dentistry | 1 | 4% |
| Unknown | 1 | 4% |
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 21 January 2014.
All research outputs
#23,213,440
of 25,870,940 outputs
Outputs from BMC Genomics
#9,972
of 11,351 outputs
Outputs of similar age
#283,676
of 323,028 outputs
Outputs of similar age from BMC Genomics
#182
of 213 outputs
Altmetric has tracked 25,870,940 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,351 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 323,028 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 213 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.