Predicting Primary Sequence-Based Protein-Protein Interactions Using a Mercer Series Representation of Nonlinear Support Vector Machine

Predicting Primary Sequence-Based Protein-Protein Interactions Using a Mercer Series Representation of Nonlinear Support Vector Machine

The prediction of protein-protein interactions (PPIs) is essential to understand the cellular processes from a medical perspective. Among the various machine learning techniques, kernel-based Support Vector Machine (SVM) has been commonly employed to discriminate between interacting and non-interact...

Full description

Bibliographic Details
Main Authors: Omid Chatrabgoun, Alireza Daneshkhah, Mohsen Esmaeilbeigi, Nader Sohrabi Safa, Ali H. Alenezi, Arafatur Rahman
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Kernel-based SVM
protein-protein interactions
quadratic optimisation problem
Mercer series
Online Access:https://ieeexplore.ieee.org/document/9956991/

Internet

https://ieeexplore.ieee.org/document/9956991/

Similar Items