ROC curves and AUC scores to compare the classifier performance of the different data sets containing various number of features.

ROC curves and AUC scores to compare the classifier performance of the different data sets containing various number of features.

<p>In total 14 features related to hyperbolic properties and centrality measures were used to predict phosphorylation and dephosphorylation directed PPIs.</p> <p>(JPG)</p>

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Bibliographic Details
Main Author:	Aimilia-Christina Vagiona (17584758) (author)
Other Authors:	Sofia Notopoulou (14256494) (author), Zbyněk Zdráhal (3324678) (author), Mariane Gonçalves-Kulik (20818278) (author), Spyros Petrakis (143222) (author), Miguel A. Andrade-Navarro (31443) (author)
Published:	2025
Subjects:	Biophysics Biochemistry Genetics Molecular Biology Cancer Biological Sciences not elsewhere classified Information Systems not elsewhere classified would allow us regulates many functions mapping contains information compact cluster composed cellular model revealed hyperbolic geometry underlying specifically interactions related random forest algorithm div >< p related directed ppis related disease network related ppis disease pathology network representation interaction network hyperbolic space hyperbolic properties protein interactions translational modification recent years ptm ). proteomics analysis predicted ptm indeed dysregulated increasing accumulation explore whether evidence supporting dysregulated ptm complex systems centrality measures
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