↓ Skip to main content

Data-intensive analysis of HIV mutations

Overview of attention for article published in BMC Bioinformatics, February 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Readers on

mendeley
22 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Data-intensive analysis of HIV mutations
Published in
BMC Bioinformatics, February 2015
DOI 10.1186/s12859-015-0452-0
Pubmed ID
Authors

Mina Cintho Ozahata, Ester Cerdeira Sabino, Ricardo Sobhie Diaz, Roberto M Cesar-, João Eduardo Ferreira

Abstract

BackgroundIn this study, clustering was performed using a bitmap representation of HIV reverse transcriptase and protease sequences, to produce an unsupervised classification of HIV sequences. The classification will aid our understanding of the interactions between mutations and drug resistance. 10,229 HIV genomic sequences from the protease and reverse transcriptase regions of the pol gene and antiretroviral resistant related mutations represented in an 82-dimensional binary vector space were analyzed.ResultsA new cluster representation was proposed using an image inspired by microarray data, such that the rows in the image represented the protein sequences from the genotype data and the columns represented presence or absence of mutations in each protein position.The visualization of the clusters showed that some mutations frequently occur together and are probably related to an epistatic phenomenon.ConclusionWe described a methodology based on the application of a pattern recognition algorithm using binary data to suggest clusters of mutations that can easily be discriminated by cluster viewing schemes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 23%
Other 2 9%
Professor > Associate Professor 2 9%
Student > Ph. D. Student 2 9%
Student > Bachelor 1 5%
Other 4 18%
Unknown 6 27%
Readers by discipline Count As %
Computer Science 5 23%
Medicine and Dentistry 3 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 9%
Agricultural and Biological Sciences 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Other 2 9%
Unknown 8 36%
Attention Score in Context

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 12 February 2015.
All research outputs
#14,213,706
of 22,786,691 outputs
Outputs from BMC Bioinformatics
#4,720
of 7,279 outputs
Outputs of similar age
#187,273
of 352,181 outputs
Outputs of similar age from BMC Bioinformatics
#78
of 134 outputs
Altmetric has tracked 22,786,691 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 31st percentile – i.e., 31% 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 352,181 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.