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Mitochondrial metagenomics: letting the genes out of the bottle

Overview of attention for article published in Giga Science, March 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

27 tweeters
1 peer review site
1 Facebook page
1 Google+ user


65 Dimensions

Readers on

180 Mendeley
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Mitochondrial metagenomics: letting the genes out of the bottle
Published in
Giga Science, March 2016
DOI 10.1186/s13742-016-0120-y
Pubmed ID

Alex Crampton-Platt, Douglas W. Yu, Xin Zhou, Alfried P. Vogler


'Mitochondrial metagenomics' (MMG) is a methodology for shotgun sequencing of total DNA from specimen mixtures and subsequent bioinformatic extraction of mitochondrial sequences. The approach can be applied to phylogenetic analysis of taxonomically selected taxa, as an economical alternative to mitogenome sequencing from individual species, or to environmental samples of mixed specimens, such as from mass trapping of invertebrates. The routine generation of mitochondrial genome sequences has great potential both for systematics and community phylogenetics. Mapping of reads from low-coverage shotgun sequencing of environmental samples also makes it possible to obtain data on spatial and temporal turnover in whole-community phylogenetic and species composition, even in complex ecosystems where species-level taxonomy and biodiversity patterns are poorly known. In addition, read mapping can produce information on species biomass, and potentially allows quantification of within-species genetic variation. The success of MMG relies on the formation of numerous mitochondrial genome contigs, achievable with standard genome assemblers, but various challenges for the efficiency of assembly remain, particularly in the face of variable relative species abundance and intra-specific genetic variation. Nevertheless, several studies have demonstrated the power of mitogenomes from MMG for accurate phylogenetic placement, evolutionary analysis of species traits, biodiversity discovery and the establishment of species distribution patterns; it offers a promising avenue for unifying the ecological and evolutionary understanding of species diversity.

Twitter Demographics

The data shown below were collected from the profiles of 27 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 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Brazil 2 1%
Netherlands 1 <1%
Australia 1 <1%
Switzerland 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Spain 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 168 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 28%
Researcher 37 21%
Student > Master 29 16%
Student > Bachelor 23 13%
Student > Postgraduate 7 4%
Other 18 10%
Unknown 16 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 94 52%
Biochemistry, Genetics and Molecular Biology 34 19%
Environmental Science 17 9%
Computer Science 4 2%
Immunology and Microbiology 3 2%
Other 5 3%
Unknown 23 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 27 February 2018.
All research outputs
of 15,799,426 outputs
Outputs from Giga Science
of 763 outputs
Outputs of similar age
of 267,285 outputs
Outputs of similar age from Giga Science
of 1 outputs
Altmetric has tracked 15,799,426 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 763 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.0. This one has gotten more attention than average, scoring higher than 58% 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 267,285 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them