Data for: hERG Liability Classification Models Using Machine Learning Techniques

Data for: hERG Liability Classification Models Using Machine Learning Techniques

This file pertains 1) all SMILES(except the evaluation set-3 which contains the compound data from in-house proprietary projects) with respective pIC50 values that were used in training and evaluating the models 2) list of descriptors that were used to build models

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Kristam, Rajendra
Format: Dataset
Sprache:eng
Schlagworte:
Cardiotoxicity
Chemoinformatics
Computational Chemistry
Long QT Syndrome
Modelling
Quantitative Structure-Activity Relationship
Toxicity
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This file pertains 1) all SMILES(except the evaluation set-3 which contains the compound data from in-house proprietary projects) with respective pIC50 values that were used in training and evaluating the models 2) list of descriptors that were used to build models
DOI:10.17632/32pdx7y72x.1