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Mendeley readers
Attention Score in Context
| Title |
TACOA – Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach
|
|---|---|
| Published in |
BMC Bioinformatics, February 2009
|
| DOI | 10.1186/1471-2105-10-56 |
| Pubmed ID | |
| Authors |
Naryttza N Diaz, Lutz Krause, Alexander Goesmann, Karsten Niehaus, Tim W Nattkemper |
| Abstract |
Metagenomics, or the sequencing and analysis of collective genomes (metagenomes) of microorganisms isolated from an environment, promises direct access to the "unculturable majority". This emerging field offers the potential to lay solid basis on our understanding of the entire living world. However, the taxonomic classification is an essential task in the analysis of metagenomics data sets that it is still far from being solved. We present a novel strategy to predict the taxonomic origin of environmental genomic fragments. The proposed classifier combines the idea of the k-nearest neighbor with strategies from kernel-based learning. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 257 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 3% |
| Brazil | 4 | 2% |
| Italy | 2 | <1% |
| Germany | 2 | <1% |
| Spain | 2 | <1% |
| Argentina | 2 | <1% |
| Canada | 2 | <1% |
| United Kingdom | 1 | <1% |
| India | 1 | <1% |
| Other | 5 | 2% |
| Unknown | 229 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 73 | 28% |
| Researcher | 61 | 24% |
| Student > Master | 34 | 13% |
| Professor > Associate Professor | 18 | 7% |
| Student > Bachelor | 17 | 7% |
| Other | 36 | 14% |
| Unknown | 18 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 144 | 56% |
| Computer Science | 33 | 13% |
| Biochemistry, Genetics and Molecular Biology | 27 | 11% |
| Immunology and Microbiology | 7 | 3% |
| Engineering | 6 | 2% |
| Other | 18 | 7% |
| Unknown | 22 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 23 June 2021.
All research outputs
#2,924,951
of 22,705,019 outputs
Outputs from BMC Bioinformatics
#1,044
of 7,254 outputs
Outputs of similar age
#15,019
of 171,699 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 54 outputs
Altmetric has tracked 22,705,019 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 7,254 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 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 171,699 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 90% of its contemporaries.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.