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Maize

Overview of attention for book
Attention for Chapter 9: Laser-Capture Microdissection of Maize Kernel Compartments for RNA-Seq-Based Expression Analysis
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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6 X users

Citations

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Chapter title
Laser-Capture Microdissection of Maize Kernel Compartments for RNA-Seq-Based Expression Analysis
Chapter number 9
Book title
Maize
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7315-6_9
Pubmed ID
Book ISBNs
978-1-4939-7314-9, 978-1-4939-7315-6
Authors

Shanshan Zhang, Dhiraj Thakare, Ramin Yadegari

Abstract

Laser-capture microdissection (LCM) enables isolation of single cells or groups of cells for a variety of downstream applications including transcriptome profiling. Recently, this methodology has found a more widespread use particularly with the advent of next-generation sequencing techniques that enable deep profiling of the limited amounts of RNA obtained from fixed or frozen sections. When used with fixed tissues, a major experimental challenge is to balance the tissue integrity needed for microscopic visualization of the cell types of interest with that of the RNA quality necessary for deep profiling. Complex biological structures such as seeds or kernels pose an especially difficult case in this context as in many instances the key internal structures such as the embryo and the endosperm are relatively inaccessible. Here, we present an optimized LCM protocol for maize kernel that has been developed specifically to enable profiling of the early stages of endosperm development using RNA-Seq.

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The data shown below were collected from the profiles of 6 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 25%
Student > Ph. D. Student 1 13%
Researcher 1 13%
Student > Doctoral Student 1 13%
Unknown 3 38%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 25%
Biochemistry, Genetics and Molecular Biology 1 13%
Social Sciences 1 13%
Design 1 13%
Unknown 3 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 13 May 2018.
All research outputs
#6,438,306
of 23,005,189 outputs
Outputs from Methods in molecular biology
#1,941
of 13,159 outputs
Outputs of similar age
#130,945
of 442,254 outputs
Outputs of similar age from Methods in molecular biology
#177
of 1,498 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 13,159 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 85% of its peers.
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 442,254 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
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 has done well, scoring higher than 88% of its contemporaries.