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Attention Score in Context
| Title |
Publication of nuclear magnetic resonance experimental data with semantic web technology and the application thereof to biomedical research of proteins
|
|---|---|
| Published in |
Journal of Biomedical Semantics, May 2016
|
| DOI | 10.1186/s13326-016-0057-1 |
| Pubmed ID | |
| Authors |
Masashi Yokochi, Naohiro Kobayashi, Eldon L. Ulrich, Akira R. Kinjo, Takeshi Iwata, Yannis E. Ioannidis, Miron Livny, John L. Markley, Haruki Nakamura, Chojiro Kojima, Toshimichi Fujiwara |
| Abstract |
The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII format have been implemented in a relational database. However, it is still fairly difficult for users to retrieve data from the NMR-STAR files or the relational database in association with data from other biological databases. To enhance the interoperability of the BMRB database, we present a full conversion of BMRB entries to two standard structured data formats, XML and RDF, as common open representations of the NMR-STAR data. Moreover, a SPARQL endpoint has been deployed. The described case study demonstrates that a simple query of the SPARQL endpoints of the BMRB, UniProt, and Online Mendelian Inheritance in Man (OMIM), can be used in NMR and structure-based analysis of proteins combined with information of single nucleotide polymorphisms (SNPs) and their phenotypes. We have developed BMRB/XML and BMRB/RDF and demonstrate their use in performing a federated SPARQL query linking the BMRB to other databases through standard semantic web technologies. This will facilitate data exchange across diverse information resources. |
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 Kingdom | 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 8% |
| Unknown | 12 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 15% |
| Researcher | 2 | 15% |
| Other | 1 | 8% |
| Student > Master | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Other | 2 | 15% |
| Unknown | 4 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 2 | 15% |
| Social Sciences | 2 | 15% |
| Computer Science | 2 | 15% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Physics and Astronomy | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 31% |
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 10 May 2016.
All research outputs
#18,456,836
of 22,869,263 outputs
Outputs from Journal of Biomedical Semantics
#299
of 364 outputs
Outputs of similar age
#218,813
of 298,934 outputs
Outputs of similar age from Journal of Biomedical Semantics
#20
of 23 outputs
Altmetric has tracked 22,869,263 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 8th percentile – i.e., 8% 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 298,934 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 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.