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NucAmino: a nucleotide to amino acid alignment optimized for virus gene sequences

Overview of attention for article published in BMC Bioinformatics, March 2017
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Title
NucAmino: a nucleotide to amino acid alignment optimized for virus gene sequences
Published in
BMC Bioinformatics, March 2017
DOI 10.1186/s12859-017-1555-6
Pubmed ID
Authors

Philip L. Tzou, Xiaoqiu Huang, Robert W. Shafer

Abstract

Current nucleotide-to-amino acid alignment software programs were developed primarily for detecting gene exons within eukaryotic genomes and were therefore optimized for speed across long genetic sequences. We developed a nucleotide-to-amino acid alignment program NucAmino optimized for virus sequencing. NucAmino is an open source program written in the high-level language Go. NucAmino is more likely to align codons flush with a reference sequence's amino acids and can be modified to facilitate the placement of insertions and deletions at specific positions. We compared NucAmino to the nucleotide to amino acid alignment program Local Alignment Program (LAP) using 115,118 human immunodeficiency virus type 1 (HIV-1) protease, reverse transcriptase, and integrase sequences-three genes that are commonly sequenced in clinical laboratories. Discordances between NucAmino and LAP occurred in 512 (16.9%) of the 3,029 sequences containing gaps but in none of 112,910 sequences without gaps. For 242 of the sequences with discordances, NucAmino produced an alignment that was preferable to that found by LAP in that it was more likely to codon align insertions and deletions and to facilitate the placement of an important drug-resistance associated insertion at the position at which most laboratories expect it to occur. NucAmino is a nucleotide-to-amino acid alignment program with several advantages for clinical laboratories performing virus sequencing compared with older programs designed for gene finding.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 27%
Other 2 13%
Student > Bachelor 2 13%
Student > Master 2 13%
Student > Ph. D. Student 1 7%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 27%
Agricultural and Biological Sciences 3 20%
Computer Science 2 13%
Immunology and Microbiology 2 13%
Unspecified 1 7%
Other 1 7%
Unknown 2 13%
Attention Score in Context

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 04 March 2017.
All research outputs
#15,448,846
of 22,958,253 outputs
Outputs from BMC Bioinformatics
#5,391
of 7,307 outputs
Outputs of similar age
#197,714
of 311,244 outputs
Outputs of similar age from BMC Bioinformatics
#89
of 138 outputs
Altmetric has tracked 22,958,253 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,307 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 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.