The application of weighted gene co-expression network analysis and support vector machine learning in the screening of Parkinson’s disease biomarkers and construction of diagnostic models
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 05 November 2023.
All research outputs
#16,783,953
of 24,753,534 outputs
Outputs from Frontiers in Molecular Neuroscience
#2,068
of 3,236 outputs
Outputs of similar age
#125,775
of 240,285 outputs
Outputs of similar age from Frontiers in Molecular Neuroscience
#28
of 41 outputs
Altmetric has tracked 24,753,534 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,236 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 35th percentile – i.e., 35% 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 240,285 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.