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Comparative analysis of tissue-specific genes in maize based on machine learning models: CNN performs technically best, LightGBM performs biologically soundest

Overview of attention for article published in Frontiers in Genetics, May 2023
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1 X user

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5 Mendeley
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Title
Comparative analysis of tissue-specific genes in maize based on machine learning models: CNN performs technically best, LightGBM performs biologically soundest
Published in
Frontiers in Genetics, May 2023
DOI 10.3389/fgene.2023.1190887
Pubmed ID
Authors

Zijie Wang, Yuzhi Zhu, Zhule Liu, Hongfu Li, Xinqiang Tang, Yi Jiang

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X Demographics

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.
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Mendeley readers

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 %
Student > Ph. D. Student 2 40%
Unspecified 1 20%
Unknown 2 40%
Readers by discipline Count As %
Unspecified 1 20%
Computer Science 1 20%
Agricultural and Biological Sciences 1 20%
Unknown 2 40%
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 10 May 2023.
All research outputs
#21,085,526
of 23,730,866 outputs
Outputs from Frontiers in Genetics
#9,069
of 12,647 outputs
Outputs of similar age
#162,675
of 206,162 outputs
Outputs of similar age from Frontiers in Genetics
#115
of 214 outputs
Altmetric has tracked 23,730,866 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,647 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% 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 206,162 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 214 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.