Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-Based Classifiers

Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-Based Classifiers

Bibliographic Details
Main Authors: Safa Haddad, Lalehan Oktay, Ismail Erol, Kader Şahin, Serdar Durdagi
Format: Article
Language:English
Published: American Chemical Society 2023-10-01
Series:ACS Omega
Online Access:https://doi.org/10.1021/acsomega.3c06074

Internet

https://doi.org/10.1021/acsomega.3c06074

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