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X Demographics
Mendeley readers
Attention Score in Context
| Title |
I-TASSER server for protein 3D structure prediction
|
|---|---|
| Published in |
BMC Bioinformatics, January 2008
|
| DOI | 10.1186/1471-2105-9-40 |
| Pubmed ID | |
| Authors |
Yang Zhang |
| Abstract |
Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 2,973 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 15 | <1% |
| United States | 14 | <1% |
| Brazil | 12 | <1% |
| Germany | 8 | <1% |
| France | 6 | <1% |
| India | 6 | <1% |
| Spain | 5 | <1% |
| Colombia | 4 | <1% |
| Poland | 3 | <1% |
| Other | 36 | 1% |
| Unknown | 2864 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 697 | 23% |
| Student > Master | 461 | 16% |
| Student > Bachelor | 390 | 13% |
| Researcher | 360 | 12% |
| Student > Doctoral Student | 172 | 6% |
| Other | 380 | 13% |
| Unknown | 513 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 877 | 29% |
| Biochemistry, Genetics and Molecular Biology | 808 | 27% |
| Chemistry | 229 | 8% |
| Immunology and Microbiology | 74 | 2% |
| Computer Science | 62 | 2% |
| Other | 326 | 11% |
| Unknown | 597 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 25 March 2021.
All research outputs
#3,422,555
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#1,089
of 7,793 outputs
Outputs of similar age
#14,087
of 172,775 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 42 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 85% 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 172,775 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.