About this document
Predicting Primary Sequence-Based Protein-Protein Interactions Using A Mercer Series Representation of Nonlinear Support Vector Machine by Korany Mahmoud is a document available to read on EtoBox.
The document discusses a novel computational algorithm for predicting protein-protein interactions (PPIs) using a low-rank truncated Mercer series representation of kernel-based Support Vector Machines (SVM). This method addresses the significant computational time issues associated with traditional kernel-based SVMs when applied to high-dimensional datasets. The proposed approach demonstrates a significant reduction in computational time while maintaining accuracy in predicting PPIs, specifically illustrat
- Author
- Korany Mahmoud
- Language
- EN