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Predicting the bioactivity of 2-alkoxycarbonylallyl esters as potential antiproliferative agents against pancreatic cancer (MiaPaCa-2) cell lines: GFA-based QSAR and ELM-based models with molecular…

Overview of attention for article published in Journal of Genetic Engineering and Biotechnology, March 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

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2 X users

Citations

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19 Dimensions

Readers on

mendeley
18 Mendeley
Title
Predicting the bioactivity of 2-alkoxycarbonylallyl esters as potential antiproliferative agents against pancreatic cancer (MiaPaCa-2) cell lines: GFA-based QSAR and ELM-based models with molecular docking
Published in
Journal of Genetic Engineering and Biotechnology, March 2021
DOI 10.1186/s43141-021-00133-2
Pubmed ID
Authors

Oluwatoba Emmanuel Oyeneyin, Babatunde Samuel Obadawo, Adesoji Alani Olanrewaju, Taoreed Olakunle Owolabi, Fahidat Adedamola Gbadamosi, Nureni Ipinloju, Helen Omonipo Modamori

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

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 3 17%
Student > Bachelor 3 17%
Student > Ph. D. Student 2 11%
Student > Master 2 11%
Professor 1 6%
Other 2 11%
Unknown 5 28%
Readers by discipline Count As %
Chemistry 3 17%
Biochemistry, Genetics and Molecular Biology 2 11%
Computer Science 2 11%
Engineering 2 11%
Sports and Recreations 1 6%
Other 2 11%
Unknown 6 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 March 2021.
All research outputs
#16,734,944
of 25,387,668 outputs
Outputs from Journal of Genetic Engineering and Biotechnology
#103
of 348 outputs
Outputs of similar age
#268,996
of 452,055 outputs
Outputs of similar age from Journal of Genetic Engineering and Biotechnology
#7
of 22 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 348 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 64% 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 452,055 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.