General Melting Point Prediction Based on a Diverse Compound Data Set and Artificial Neural Networks

Abstract

We report the development of a robust and general model for the prediction of melting points. It is based on a diverse data set of 4173 compounds and employs a large number of 2D and 3D descriptors to capture molecular physicochemical and other graph-based properties. Dimensionality reduction is performed by principal component analysis, while a fully… (More)
DOI: 10.1021/ci0500132

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