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Validation of reference genes aiming accurate normalization of qPCR data in soybean upon nematode parasitism and insect attack

Overview of attention for article published in BMC Research Notes, May 2013
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1 tweeter

Citations

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50 Mendeley

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Title
Validation of reference genes aiming accurate normalization of qPCR data in soybean upon nematode parasitism and insect attack
Published in
BMC Research Notes, May 2013
DOI 10.1186/1756-0500-6-196
Pubmed ID
23668315
Authors

Vívian de Jesus Miranda, Roberta Ramos Coelho, Antônio Américo Barbosa Viana, Osmundo Brilhante de Oliveira Neto, Regina Maria Dechechi Gomes Carneiro, Thales Lima Rocha, Maria Fatima Grossi de Sa, Rodrigo Rocha Fragoso

Abstract

Soybean pathogens and pests reduce grain production worldwide. Biotic interaction cause extensive changes in plant gene expression profile and the data produced by functional genomics studies need validation, usually done by quantitative PCR. Nevertheless, this technique relies on accurate normalization which, in turn, depends upon the proper selection of stable reference genes for each experimental condition. To date, only a few studies were performed to validate reference genes in soybean subjected to biotic stress. Here, we report reference genes validation in soybean during root-knot nematode (Meloidogyne incognita) parasitism and velvetbean caterpillar (Anticarsia gemmatalis) attack.

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Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Belgium 1 2%
Taiwan 1 2%
Brazil 1 2%
Unknown 46 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 24%
Student > Ph. D. Student 11 22%
Student > Master 7 14%
Student > Doctoral Student 5 10%
Student > Postgraduate 3 6%
Other 8 16%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 72%
Biochemistry, Genetics and Molecular Biology 6 12%
Unspecified 1 2%
Computer Science 1 2%
Chemistry 1 2%
Other 0 0%
Unknown 5 10%

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 May 2013.
All research outputs
#18,339,860
of 22,711,242 outputs
Outputs from BMC Research Notes
#3,009
of 4,256 outputs
Outputs of similar age
#145,232
of 193,259 outputs
Outputs of similar age from BMC Research Notes
#50
of 58 outputs
Altmetric has tracked 22,711,242 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 4,256 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 16th percentile – i.e., 16% 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 193,259 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.

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