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Attention Score in Context
Chapter title |
RNA-Seq Analysis of the Transcriptome of Leaf Senescence in Tobacco
|
---|---|
Chapter number | 27 |
Book title |
Plant Senescence
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7672-0_27 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7670-6, 978-1-4939-7672-0
|
Authors |
Wei Li, Yongfeng Guo |
Abstract |
Leaf senescence is a complex developmental process which is under the control of a highly regulated genetic program and involves major changes in gene expression. During the past two decades, significant progress in molecular understanding of leaf senescence has been made through transcriptomic analysis, which, in comparison with traditional molecular biology, provides enormous amount of information on gene expression regulation at the whole genome level. In this chapter, we describe the protocol for RNA-seq, one of the most commonly used technologies in transcriptomic analysis, using tobacco leaf senescence as a model system. |
X Demographics
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 5 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 3 | 60% |
Student > Ph. D. Student | 1 | 20% |
Student > Doctoral Student | 1 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 3 | 60% |
Biochemistry, Genetics and Molecular Biology | 1 | 20% |
Unknown | 1 | 20% |
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 03 February 2018.
All research outputs
#15,490,822
of 23,020,670 outputs
Outputs from Methods in molecular biology
#5,388
of 13,166 outputs
Outputs of similar age
#269,787
of 442,354 outputs
Outputs of similar age from Methods in molecular biology
#596
of 1,498 outputs
Altmetric has tracked 23,020,670 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 13,166 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.