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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments
|
|---|---|
| Published in |
BMC Bioinformatics, February 2016
|
| DOI | 10.1186/s12859-016-0930-z |
| Pubmed ID | |
| Authors |
Jeff Daily |
| Abstract |
Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. A faster intra-sequence local pairwise alignment implementation is described and benchmarked, including new global and semi-global variants. Using a 375 residue query sequence a speed of 136 billion cell updates per second (GCUPS) was achieved on a dual Intel Xeon E5-2670 24-core processor system, the highest reported for an implementation based on Farrar's 'striped' approach. Rognes's SWIPE optimal database search application is still generally the fastest available at 1.2 to at best 2.4 times faster than Parasail for sequences shorter than 500 amino acids. However, Parasail was faster for longer sequences. For global alignments, Parasail's prefix scan implementation is generally the fastest, faster even than Farrar's 'striped' approach, however the opal library is faster for single-threaded applications. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. Applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | 1% |
| France | 1 | 1% |
| Belgium | 1 | 1% |
| Unknown | 84 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 22% |
| Researcher | 18 | 21% |
| Student > Master | 14 | 16% |
| Student > Bachelor | 4 | 5% |
| Professor > Associate Professor | 3 | 3% |
| Other | 9 | 10% |
| Unknown | 20 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 22 | 25% |
| Biochemistry, Genetics and Molecular Biology | 20 | 23% |
| Agricultural and Biological Sciences | 13 | 15% |
| Engineering | 3 | 3% |
| Chemistry | 3 | 3% |
| Other | 2 | 2% |
| Unknown | 24 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 09 March 2017.
All research outputs
#13,900,658
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#4,306
of 7,418 outputs
Outputs of similar age
#197,758
of 403,900 outputs
Outputs of similar age from BMC Bioinformatics
#89
of 141 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.