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Transcriptome analysis of rice root heterosis by RNA-Seq

Overview of attention for article published in BMC Genomics, January 2013
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Title
Transcriptome analysis of rice root heterosis by RNA-Seq
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-19
Pubmed ID
Authors

Rongrong Zhai, Yue Feng, Huimin Wang, Xiaodeng Zhan, Xihong Shen, Weiming Wu, Yingxin Zhang, Daibo Chen, Gaoxing Dai, Zhanlie Yang, Liyong Cao, Shihua Cheng

Abstract

Heterosis is a phenomenon in which hybrids exhibit superior performance relative to parental phenotypes. In addition to the heterosis of above-ground agronomic traits on which most existing studies have focused, root heterosis is also an indispensable component of heterosis in the entire plant and of major importance to plant breeding. Consequently, systematic investigations of root heterosis, particularly in reproductive-stage rice, are needed. The recent advent of RNA sequencing technology (RNA-Seq) provides an opportunity to conduct in-depth transcript profiling for heterosis studies.

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

Geographical breakdown

Country Count As %
United States 3 2%
China 2 1%
United Kingdom 1 <1%
Brazil 1 <1%
India 1 <1%
Mexico 1 <1%
Unknown 145 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 31%
Researcher 38 25%
Student > Master 14 9%
Student > Doctoral Student 11 7%
Student > Postgraduate 7 5%
Other 12 8%
Unknown 25 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 98 64%
Biochemistry, Genetics and Molecular Biology 18 12%
Environmental Science 3 2%
Pharmacology, Toxicology and Pharmaceutical Science 1 <1%
Unspecified 1 <1%
Other 4 3%
Unknown 29 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 05 June 2013.
All research outputs
#15,272,977
of 22,711,645 outputs
Outputs from BMC Genomics
#6,668
of 10,626 outputs
Outputs of similar age
#184,252
of 285,031 outputs
Outputs of similar age from BMC Genomics
#234
of 364 outputs
Altmetric has tracked 22,711,645 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 10,626 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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We're also able to compare this research output to 364 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.