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Characterization of a transcriptome from a non-model organism, Cladonia rangiferina, the grey reindeer lichen, using high-throughput next generation sequencing and EST sequence data

Overview of attention for article published in BMC Genomics, October 2012
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Title
Characterization of a transcriptome from a non-model organism, Cladonia rangiferina, the grey reindeer lichen, using high-throughput next generation sequencing and EST sequence data
Published in
BMC Genomics, October 2012
DOI 10.1186/1471-2164-13-575
Pubmed ID
Authors

Sini Junttila, Stephen Rudd

Abstract

Lichens are symbiotic organisms that have a remarkable ability to survive in some of the most extreme terrestrial climates on earth. Lichens can endure frequent desiccation and wetting cycles and are able to survive in a dehydrated molecular dormant state for decades at a time. Genetic resources have been established in lichen species for the study of molecular systematics and their taxonomic classification. No lichen species have been characterised yet using genomics and the molecular mechanisms underlying the lichen symbiosis and the fundamentals of desiccation tolerance remain undescribed. We report the characterisation of a transcriptome of the grey reindeer lichen, Cladonia rangiferina, using high-throughput next-generation transcriptome sequencing and traditional Sanger EST sequencing data.

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The data shown below were collected from the profiles of 2 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 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 2 3%
Spain 1 1%
Australia 1 1%
Unknown 74 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 21%
Student > Ph. D. Student 15 19%
Student > Master 11 14%
Student > Bachelor 10 13%
Student > Doctoral Student 6 8%
Other 12 15%
Unknown 8 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 64%
Biochemistry, Genetics and Molecular Biology 9 12%
Environmental Science 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Arts and Humanities 1 1%
Other 7 9%
Unknown 8 10%
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 23 December 2020.
All research outputs
#19,962,154
of 25,394,764 outputs
Outputs from BMC Genomics
#8,142
of 11,250 outputs
Outputs of similar age
#152,500
of 202,202 outputs
Outputs of similar age from BMC Genomics
#148
of 198 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,250 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 198 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.