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Genomic resources for a model in adaptation and speciation research: characterization of the Poecilia mexicana transcriptome

Overview of attention for article published in BMC Genomics, November 2012
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Title
Genomic resources for a model in adaptation and speciation research: characterization of the Poecilia mexicana transcriptome
Published in
BMC Genomics, November 2012
DOI 10.1186/1471-2164-13-652
Pubmed ID
Authors

Joanna L Kelley, Courtney N Passow, Martin Plath, Lenin Arias Rodriguez, Muh-Ching Yee, Michael Tobler

Abstract

Elucidating the genomic basis of adaptation and speciation is a major challenge in natural systems with large quantities of environmental and phenotypic data, mostly because of the scarcity of genomic resources for non-model organisms. The Atlantic molly (Poecilia mexicana, Poeciliidae) is a small livebearing fish that has been extensively studied for evolutionary ecology research, particularly because this species has repeatedly colonized extreme environments in the form of caves and toxic hydrogen sulfide containing springs. In such extreme environments, populations show strong patterns of adaptive trait divergence and the emergence of reproductive isolation. Here, we used RNA-sequencing to assemble and annotate the first transcriptome of P. mexicana to facilitate ecological genomics studies in the future and aid the identification of genes underlying adaptation and speciation in the system.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Spain 1 <1%
Italy 1 <1%
Australia 1 <1%
Unknown 101 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 26%
Researcher 20 19%
Student > Master 14 13%
Student > Bachelor 7 7%
Other 6 6%
Other 18 17%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 49%
Biochemistry, Genetics and Molecular Biology 19 18%
Environmental Science 6 6%
Psychology 3 3%
Social Sciences 2 2%
Other 6 6%
Unknown 18 17%
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 21 November 2012.
All research outputs
#22,758,309
of 25,371,288 outputs
Outputs from BMC Genomics
#9,840
of 11,244 outputs
Outputs of similar age
#255,335
of 285,348 outputs
Outputs of similar age from BMC Genomics
#179
of 196 outputs
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So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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