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Analysis of the leaf transcriptome of Musa acuminata during interaction with Mycosphaerella musicola: gene assembly, annotation and marker development

Overview of attention for article published in BMC Genomics, February 2013
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Title
Analysis of the leaf transcriptome of Musa acuminata during interaction with Mycosphaerella musicola: gene assembly, annotation and marker development
Published in
BMC Genomics, February 2013
DOI 10.1186/1471-2164-14-78
Pubmed ID
Authors

Marco A N Passos, Viviane Oliveira de Cruz, Flavia L Emediato, Cristiane Camargo de Teixeira, Vânia C Rennó Azevedo, Ana C M Brasileiro, Edson P Amorim, Claudia F Ferreira, Natalia F Martins, Roberto C Togawa, Georgios J Pappas Júnior, Orzenil Bonfim da Silva, Robert NG Miller

Abstract

Although banana (Musa sp.) is an important edible crop, contributing towards poverty alleviation and food security, limited transcriptome datasets are available for use in accelerated molecular-based breeding in this genus. 454 GS-FLX Titanium technology was employed to determine the sequence of gene transcripts in genotypes of Musa acuminata ssp. burmannicoides Calcutta 4 and M. acuminata subgroup Cavendish cv. Grande Naine, contrasting in resistance to the fungal pathogen Mycosphaerella musicola, causal organism of Sigatoka leaf spot disease. To enrich for transcripts under biotic stress responses, full length-enriched cDNA libraries were prepared from whole plant leaf materials, both uninfected and artificially challenged with pathogen conidiospores.

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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 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ethiopia 1 <1%
France 1 <1%
Australia 1 <1%
Unknown 136 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 20%
Student > Ph. D. Student 27 19%
Student > Master 22 16%
Student > Bachelor 12 9%
Student > Doctoral Student 10 7%
Other 22 16%
Unknown 18 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 83 60%
Biochemistry, Genetics and Molecular Biology 11 8%
Environmental Science 3 2%
Computer Science 2 1%
Economics, Econometrics and Finance 2 1%
Other 12 9%
Unknown 26 19%
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 06 February 2013.
All research outputs
#18,327,422
of 22,694,633 outputs
Outputs from BMC Genomics
#8,146
of 10,616 outputs
Outputs of similar age
#219,339
of 282,906 outputs
Outputs of similar age from BMC Genomics
#278
of 366 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 282,906 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 366 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.