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muBLASTP: database-indexed protein sequence search on multicore CPUs

Overview of attention for article published in BMC Bioinformatics, November 2016
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2 tweeters

Citations

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9 Dimensions

Readers on

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27 Mendeley
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Title
muBLASTP: database-indexed protein sequence search on multicore CPUs
Published in
BMC Bioinformatics, November 2016
DOI 10.1186/s12859-016-1302-4
Pubmed ID
Authors

Jing Zhang, Sanchit Misra, Hao Wang, Wu-chun Feng

Abstract

The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search. muBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST. With a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 4%
France 1 4%
Unknown 25 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 48%
Other 2 7%
Student > Doctoral Student 2 7%
Professor 2 7%
Student > Master 2 7%
Other 5 19%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 41%
Biochemistry, Genetics and Molecular Biology 6 22%
Engineering 3 11%
Computer Science 2 7%
Medicine and Dentistry 1 4%
Other 2 7%
Unknown 2 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 November 2016.
All research outputs
#4,632,564
of 8,597,853 outputs
Outputs from BMC Bioinformatics
#2,554
of 3,722 outputs
Outputs of similar age
#136,678
of 246,717 outputs
Outputs of similar age from BMC Bioinformatics
#72
of 133 outputs
Altmetric has tracked 8,597,853 research outputs across all sources so far. This one is in the 27th percentile – i.e., 27% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,722 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 246,717 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.