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An efficient method for stable protein targeting in grasses (Poaceae): a case study in Puccinellia tenuiflora

Overview of attention for article published in BMC Biotechnology, June 2014
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Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
9 Mendeley
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Title
An efficient method for stable protein targeting in grasses (Poaceae): a case study in Puccinellia tenuiflora
Published in
BMC Biotechnology, June 2014
DOI 10.1186/1472-6750-14-52
Pubmed ID
Authors

Yuanyuan Bu, Mengqing Zhao, Bo Sun, Xinxin Zhang, Tetsuo Takano, Shenkui Liu

Abstract

An efficient transformation method is lacking for most non-model plant species to test gene function. Therefore, subcellular localization of proteins of interest from non-model plants is mainly carried out through transient transformation in homologous cells or in heterologous cells from model species such as Arabidopsis. Although analysis of expression patterns in model organisms like yeast and Arabidopsis can provide important clues about protein localization, these heterologous systems may not always faithfully reflect the native subcellular distribution in other species. On the other hand, transient expression in protoplasts from species of interest has limited ability for detailed sub-cellular localization analysis (e.g., those involving subcellular fractionation or sectioning and immunodetection), as it results in heterogeneous populations comprised of both transformed and untransformed cells.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 22%
Researcher 2 22%
Other 1 11%
Professor 1 11%
Student > Doctoral Student 1 11%
Other 2 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 56%
Biochemistry, Genetics and Molecular Biology 2 22%
Social Sciences 1 11%
Unknown 1 11%

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 June 2014.
All research outputs
#3,704,869
of 5,565,938 outputs
Outputs from BMC Biotechnology
#337
of 424 outputs
Outputs of similar age
#83,010
of 133,283 outputs
Outputs of similar age from BMC Biotechnology
#19
of 29 outputs
Altmetric has tracked 5,565,938 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 424 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 18th percentile – i.e., 18% 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 133,283 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.