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Digital Gene Expression Analysis Based on Integrated De Novo Transcriptome Assembly of Sweet Potato [Ipomoea batatas (L.) Lam.]

Overview of attention for article published in PLOS ONE, April 2012
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Citations

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Title
Digital Gene Expression Analysis Based on Integrated De Novo Transcriptome Assembly of Sweet Potato [Ipomoea batatas (L.) Lam.]
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0036234
Pubmed ID
Authors

Xiang Tao, Ying-Hong Gu, Hai-Yan Wang, Wen Zheng, Xiao Li, Chuan-Wu Zhao, Yi-Zheng Zhang

Abstract

Sweet potato (Ipomoea batatas L. [Lam.]) ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages.

X Demographics

X Demographics

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

Geographical breakdown

Country Count As %
United Kingdom 2 1%
China 2 1%
Kenya 1 <1%
Sweden 1 <1%
Austria 1 <1%
Slovakia 1 <1%
Chile 1 <1%
Slovenia 1 <1%
United States 1 <1%
Other 0 0%
Unknown 185 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 26%
Researcher 42 21%
Student > Master 20 10%
Student > Doctoral Student 17 9%
Student > Postgraduate 9 5%
Other 32 16%
Unknown 25 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 123 63%
Biochemistry, Genetics and Molecular Biology 20 10%
Computer Science 3 2%
Chemistry 3 2%
Nursing and Health Professions 2 1%
Other 13 7%
Unknown 32 16%
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 30 April 2012.
All research outputs
#15,243,120
of 22,664,644 outputs
Outputs from PLOS ONE
#129,812
of 193,509 outputs
Outputs of similar age
#104,291
of 163,320 outputs
Outputs of similar age from PLOS ONE
#2,379
of 3,700 outputs
Altmetric has tracked 22,664,644 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,509 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 24th percentile – i.e., 24% 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 163,320 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,700 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.