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Mendeley readers
Attention Score in Context
| Title |
ArrayTrack: a free FDA bioinformatics tool to support emerging biomedical research -- an update
|
|---|---|
| Published in |
Human Genomics, August 2010
|
| DOI | 10.1186/1479-7364-4-6-428 |
| Pubmed ID | |
| Authors |
Joshua Xu, Reagan Kelly, Hong Fang, Weida Tong |
| Abstract |
ArrayTrack is a Food and Drug Administration (FDA) bioinformatics tool that has been widely adopted by the research community for genomics studies. It provides an integrated environment for microarray data management, analysis and interpretation. Most of its functionality for statistical, pathway and gene ontology analysis can also be applied independently to data generated by other molecular technologies. ArrayTrack has been undergoing active development and enhancement since its inception in 2001. This review summarises its key functionalities, with emphasis on the most recent extensions in support of the evolving needs of FDA's research programmes. ArrayTrack has added capability to manage, analyse and interpret proteomics and metabolomics data after quantification of peptides and metabolites abundance, respectively. Annotation information about single nucleotide polymorphisms and quantitative trait loci has been integrated to support genetics-related studies. Other extensions have been added to manage and analyse genomics data related to bacterial food-borne pathogens. |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 5% |
| United States | 1 | 5% |
| Unknown | 17 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 21% |
| Professor > Associate Professor | 3 | 16% |
| Professor | 3 | 16% |
| Student > Master | 2 | 11% |
| Student > Bachelor | 2 | 11% |
| Other | 4 | 21% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 26% |
| Medicine and Dentistry | 3 | 16% |
| Engineering | 3 | 16% |
| Computer Science | 2 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 4 | 21% |
| Unknown | 1 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 October 2013.
All research outputs
#8,537,346
of 25,377,790 outputs
Outputs from Human Genomics
#211
of 564 outputs
Outputs of similar age
#37,975
of 103,891 outputs
Outputs of similar age from Human Genomics
#2
of 4 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has gotten more attention than average, scoring higher than 53% 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 103,891 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.