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X Demographics
Mendeley readers
Attention Score in Context
| Title |
OrfM: a fast open reading frame predictor for metagenomic data
|
|---|---|
| Published in |
Bioinformatics, May 2016
|
| DOI | 10.1093/bioinformatics/btw241 |
| Pubmed ID | |
| Authors |
Ben J Woodcroft, Joel A Boyd, Gene W Tyson |
| Abstract |
Finding and translating stretches of DNA lacking stop codons is a task common in the analysis of sequence data. However the computational tools for finding open reading frames are sufficiently slow that they are becoming a bottleneck as the volume of sequence data grows. This computational bottleneck is especially problematic in metagenomics when searching unassembled reads, or screening assembled contigs for genes of interest. Here we present OrfM, a tool to rapidly identify open reading frames (ORFs) in sequence data by applying the Aho-Corasick algorithm to find regions uninterrupted by stop codons. Benchmarking revealed that OrfM finds identical ORFs to similar tools ('GetOrf' and 'Translate') but is five times faster. While OrfM is sequencing platform-agnostic, it is best suited to large, high quality datasets such as those produced by Illumina sequencers. Source code and binaries freely available for download at http://github.com/wwood/OrfM or through GNU Guix under the LGPL 3+ license, implemented in C and supported on GNU/Linux and OSX. [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
X Demographics
The data shown below were collected from the profiles of 19 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 | 6 | 32% |
| United Kingdom | 2 | 11% |
| Australia | 2 | 11% |
| Norway | 1 | 5% |
| Canada | 1 | 5% |
| Mexico | 1 | 5% |
| Spain | 1 | 5% |
| Taiwan | 1 | 5% |
| Unknown | 4 | 21% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 11 | 58% |
| Members of the public | 8 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 2% |
| Australia | 1 | <1% |
| Norway | 1 | <1% |
| Sweden | 1 | <1% |
| Canada | 1 | <1% |
| New Zealand | 1 | <1% |
| Japan | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 107 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 25% |
| Researcher | 20 | 17% |
| Student > Master | 20 | 17% |
| Student > Bachelor | 10 | 9% |
| Student > Doctoral Student | 7 | 6% |
| Other | 14 | 12% |
| Unknown | 16 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 35 | 30% |
| Biochemistry, Genetics and Molecular Biology | 33 | 28% |
| Environmental Science | 7 | 6% |
| Computer Science | 6 | 5% |
| Immunology and Microbiology | 5 | 4% |
| Other | 13 | 11% |
| Unknown | 17 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 05 January 2023.
All research outputs
#1,648,313
of 25,374,647 outputs
Outputs from Bioinformatics
#845
of 12,808 outputs
Outputs of similar age
#26,910
of 312,398 outputs
Outputs of similar age from Bioinformatics
#29
of 217 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 93% 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 312,398 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 217 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.