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MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads

Overview of attention for article published in Source Code for Biology and Medicine, December 2012
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Citations

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3 Dimensions

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73 Mendeley
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3 CiteULike
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Title
MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads
Published in
Source Code for Biology and Medicine, December 2012
DOI 10.1186/1751-0473-7-13
Pubmed ID
Authors

Alexander V Tyakht, Anna S Popenko, Maxim S Belenikin, Ilya A Altukhov, Alexander V Pavlenko, Elena S Kostryukova, Oksana V Selezneva, Andrei K Larin, Irina Y Karpova, Dmitry G Alexeev

Abstract

MALINA is a web service for bioinformatic analysis of whole-genome metagenomic data obtained from human gut microbiota sequencing. As input data, it accepts metagenomic reads of various sequencing technologies, including long reads (such as Sanger and 454 sequencing) and next-generation (including SOLiD and Illumina). It is the first metagenomic web service that is capable of processing SOLiD color-space reads, to authors' knowledge. The web service allows phylogenetic and functional profiling of metagenomic samples using coverage depth resulting from the alignment of the reads to the catalogue of reference sequences which are built into the pipeline and contain prevalent microbial genomes and genes of human gut microbiota. The obtained metagenomic composition vectors are processed by the statistical analysis and visualization module containing methods for clustering, dimension reduction and group comparison. Additionally, the MALINA database includes vectors of bacterial and functional composition for human gut microbiota samples from a large number of existing studies allowing their comparative analysis together with user samples, namely datasets from Russian Metagenome project, MetaHIT and Human Microbiome Project (downloaded from http://hmpdacc.org). MALINA is made freely available on the web at http://malina.metagenome.ru. The website is implemented in JavaScript (using Ext JS), Microsoft .NET Framework, MS SQL, Python, with all major browsers supported.

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The data shown below were collected from the profiles of 5 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 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Germany 1 1%
Norway 1 1%
Sweden 1 1%
Brazil 1 1%
Russia 1 1%
United Kingdom 1 1%
Unknown 64 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 27%
Student > Ph. D. Student 18 25%
Student > Bachelor 6 8%
Professor > Associate Professor 6 8%
Professor 5 7%
Other 11 15%
Unknown 7 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 40%
Computer Science 13 18%
Biochemistry, Genetics and Molecular Biology 9 12%
Immunology and Microbiology 3 4%
Engineering 3 4%
Other 5 7%
Unknown 11 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 December 2012.
All research outputs
#12,866,358
of 22,689,790 outputs
Outputs from Source Code for Biology and Medicine
#53
of 127 outputs
Outputs of similar age
#151,329
of 277,812 outputs
Outputs of similar age from Source Code for Biology and Medicine
#2
of 5 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has gotten more attention than average, scoring higher than 55% 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 277,812 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 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.