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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mining for class-specific motifs in protein sequence classification
|
|---|---|
| Published in |
BMC Bioinformatics, March 2013
|
| DOI | 10.1186/1471-2105-14-96 |
| Pubmed ID | |
| Authors |
Satish M Srinivasan, Suleyman Vural, Brian R King, Chittibabu Guda |
| Abstract |
In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. |
X Demographics
The data shown below were collected from the profiles of 6 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 | 33% |
| Switzerland | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 2% |
| Switzerland | 1 | 2% |
| Brazil | 1 | 2% |
| Russia | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 50 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 33% |
| Student > Master | 9 | 16% |
| Researcher | 5 | 9% |
| Student > Bachelor | 5 | 9% |
| Lecturer | 4 | 7% |
| Other | 6 | 11% |
| Unknown | 8 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 27% |
| Computer Science | 14 | 25% |
| Biochemistry, Genetics and Molecular Biology | 6 | 11% |
| Neuroscience | 3 | 5% |
| Chemistry | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 10 | 18% |
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 19 March 2013.
All research outputs
#6,922,951
of 22,701,287 outputs
Outputs from BMC Bioinformatics
#2,683
of 7,254 outputs
Outputs of similar age
#58,797
of 196,095 outputs
Outputs of similar age from BMC Bioinformatics
#56
of 146 outputs
Altmetric has tracked 22,701,287 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 7,254 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 61% 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 196,095 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 68% of its contemporaries.
We're also able to compare this research output to 146 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 56% of its contemporaries.