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

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1. Verfasser:	Kristam, Rajendra
Format:	Dataset
Sprache:	eng
Schlagworte:	Cardiotoxicity Chemoinformatics Computational Chemistry Long QT Syndrome Modelling Quantitative Structure-Activity Relationship Toxicity
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creator	Kristam, Rajendra
description	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_str_mv	10.17632/32pdx7y72x.1
format	Dataset
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identifier	DOI: 10.17632/32pdx7y72x.1
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language	eng
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subjects	Cardiotoxicity Chemoinformatics Computational Chemistry Long QT Syndrome Modelling Quantitative Structure-Activity Relationship Toxicity
title	Data for: hERG Liability Classification Models Using Machine Learning Techniques
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