drug discovery 1molecular descriptors 1qsar modeling 1quantum kernel learning 1quantum support vector machine 1
From the 1 of 3 linked papers with an AI index.
3 papers
quant-ph2026
: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning
Mariano Caruso, Daniel Ruiz, Alejandro Giraldo +1
The paper introduces Q^2SAR, a quantum multiple kernel learning framework that uses quantum support vector machines to improve QSAR predictions for drug discovery, demonstrating hi…
quant-ph2025
Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery
Alejandro Giraldo, Daniel Ruiz, Mariano Caruso +2
Quantitative Structure-Activity Relationship (QSAR) modeling is a cornerstone of computational drug discovery. This research demonstrates the successful application of a Quantum Mu…
quant-ph2025
Quantum QSAR for drug discovery
Alejandro Giraldo, Daniel Ruiz, Mariano Caruso +1
Quantitative Structure-Activity Relationship (QSAR) modeling is key in drug discovery, but classical methods face limitations when handling high-dimensional data and capturing comp…