↓ Skip to main content

DensePPI: A Novel Image-Based Deep Learning Method for Prediction of Protein–Protein Interactions

Overview of attention for article published in IEEE Transactions on NanoBioscience, October 2023
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
7 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
DensePPI: A Novel Image-Based Deep Learning Method for Prediction of Protein–Protein Interactions
Published in
IEEE Transactions on NanoBioscience, October 2023
DOI 10.1109/tnb.2023.3251192
Pubmed ID
Authors

Aanzil Akram Halsana, Tapas Chakroborty, Anup Kumar Halder, Subhadip Basu

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

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Researcher 1 14%
Unknown 4 57%
Readers by discipline Count As %
Computer Science 3 43%
Biochemistry, Genetics and Molecular Biology 1 14%
Unknown 3 43%
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 08 April 2023.
All research outputs
#16,737,737
of 25,394,764 outputs
Outputs from IEEE Transactions on NanoBioscience
#193
of 371 outputs
Outputs of similar age
#183,178
of 354,949 outputs
Outputs of similar age from IEEE Transactions on NanoBioscience
#1
of 6 outputs
Altmetric has tracked 25,394,764 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 371 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 46th percentile – i.e., 46% 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 354,949 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them