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A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer

Overview of attention for article published in Frontiers in Molecular Biosciences, January 2023
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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2 X users

Citations

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2 Dimensions

Readers on

mendeley
6 Mendeley
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Title
A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer
Published in
Frontiers in Molecular Biosciences, January 2023
DOI 10.3389/fmolb.2023.1094321
Pubmed ID
Authors

Sung-Young Shin, Margaret M. Centenera, Joshua T. Hodgson, Elizabeth V. Nguyen, Lisa M. Butler, Roger J. Daly, Lan K. Nguyen

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

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 17%
Researcher 1 17%
Unknown 4 67%
Readers by discipline Count As %
Unspecified 1 17%
Medicine and Dentistry 1 17%
Unknown 4 67%
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 06 February 2023.
All research outputs
#19,133,656
of 23,709,010 outputs
Outputs from Frontiers in Molecular Biosciences
#2,099
of 4,142 outputs
Outputs of similar age
#299,318
of 435,782 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#123
of 258 outputs
Altmetric has tracked 23,709,010 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,142 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 34th percentile – i.e., 34% 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 435,782 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 258 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.