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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FAST: FAST Analysis of Sequences Toolbox
|
|---|---|
| Published in |
Frontiers in Genetics, May 2015
|
| DOI | 10.3389/fgene.2015.00172 |
| Pubmed ID | |
| Authors |
Travis J. Lawrence, Kyle T. Kauffman, Katherine C. H. Amrine, Dana L. Carper, Raymond S. Lee, Peter J. Becich, Claudia J. Canales, David H. Ardell |
| Abstract |
FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought. |
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% |
| Sri Lanka | 1 | 17% |
| Canada | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 2% |
| France | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 61 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 25% |
| Student > Ph. D. Student | 14 | 22% |
| Student > Master | 11 | 17% |
| Student > Bachelor | 6 | 9% |
| Professor > Associate Professor | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 2 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 20 | 31% |
| Agricultural and Biological Sciences | 20 | 31% |
| Computer Science | 5 | 8% |
| Engineering | 3 | 5% |
| Veterinary Science and Veterinary Medicine | 1 | 2% |
| Other | 8 | 13% |
| Unknown | 7 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 01 June 2016.
All research outputs
#6,281,635
of 23,577,761 outputs
Outputs from Frontiers in Genetics
#1,805
of 12,603 outputs
Outputs of similar age
#71,929
of 267,766 outputs
Outputs of similar age from Frontiers in Genetics
#38
of 108 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 12,603 research outputs from this source. They receive a mean Attention Score of 3.7. 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 267,766 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 72% of its contemporaries.
We're also able to compare this research output to 108 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 62% of its contemporaries.