Our Datasets and Results From Our Study: GGL-PPI Models

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Our Datasets and Results From Our Study: GGL-PPI Models
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In this section, we perform validation and evaluation of our proposed models on several benchmark datasets. We develop two types of GGL-PPI models

This paper is available on arxiv under CC 4.0 license. Authors: Md Masud Rana, Department of Mathematics, University of Kentucky; Duc Duy Nguyen, Department of Mathematics, University of Kentucky & [email protected]. Table of Links Abstract & Introduction Datasets and Results Methods Conclusion, Data and Software Availability, Competing interests, Acknowledgments & References 2 Datasets and Results : GGL-PPI1 and GGL-PPI2.

Notably, the authors of the mCSM-PPI2 method filtered the single-point mutations, yielding S4169 set, comprising 4,169 variants in 139 different complexes/ The S8338 set, derived from S4169, represents hypothetical reverse mutation energy changes with negative values. This comprehensive dataset serves as a valuable resource for studying protein interactions and their thermodynamic properties. Perforamnce-wise, Our GGL-PPI2 model posts an Rp of 0.81 with an RMSE of 1.

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