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

ŞAHİN KADER,DURDAĞI SERDAR

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

YAYIN ID:

9041737

KAPSAM AD:

Uluslararası

HAKEM TUR AD:

Hakemli

ENDEKS:

SCI-Expanded

MAKALE ADI:

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

YAZAR ADI:

ŞAHİN KADER,DURDAĞI SERDAR

DERGI ADI:

ACS Omega

YAYIN DILI ADI:

Türkçe

AY:

YIL:

2023

CILT:

SAYI:

ILK SAYFA:

SON SAYFA:

ISSN:

2470-1343

ERISIM TURU AD:

Basılı+Elektronik

ALAN BILGISI:

Fen Bilimleri ve Matematik Temel Alanı>Kimya

YAZAR ID:

7970070

GUNCELLEME TARIHI:

2024-07-18 14:56:40

MAKALE TURU AD:

Özgün Makale

ERISIM LINKI:

http://dx.doi.org/10.1021/acsomega.3c06074