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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, January 2013
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1 tweeter

Citations

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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, January 2013
DOI 10.1186/1756-0500-6-196
Pubmed ID
Authors

Vívian de Miranda, Roberta Coelho, Antônio Américo Viana, Osmundo de Oliveira Neto, Regina Maria Dechechi Carneiro, Thales Rocha, Maria Grossi de Sa, Rodrigo 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.

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

Geographical breakdown

Country Count As %
Spain 1 3%
Brazil 1 3%
Taiwan 1 3%
Belgium 1 3%
Unknown 36 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 25%
Student > Ph. D. Student 8 20%
Student > Master 6 15%
Student > Doctoral Student 5 13%
Student > Postgraduate 3 8%
Other 8 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 83%
Biochemistry, Genetics and Molecular Biology 4 10%
Unspecified 2 5%
Computer Science 1 3%

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
#10,018,171
of 12,519,627 outputs
Outputs from BMC Research Notes
#1,940
of 2,804 outputs
Outputs of similar age
#102,637
of 147,654 outputs
Outputs of similar age from BMC Research Notes
#4
of 4 outputs
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So far Altmetric has tracked 2,804 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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