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Literature DB >> 17576646

Predicting lipophilicity of drug-discovery molecules using Gaussian process models.

Timon S Schroeter¹, Anton Schwaighofer, Sebastian Mika, Antonius Ter Laak, Detlev Suelzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller.

Abstract

Mesh：

Year: 2007 PMID： 17576646 DOI： 10.1002/cmdc.200700041

Source DB: PubMed Journal: ChemMedChem ISSN： 1860-7179 Impact factor: 3.466

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5 in total

1. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

Authors: Timon Sebastian Schroeter; Anton Schwaighofer; Sebastian Mika; Antonius Ter Laak; Detlev Suelzle; Ursula Ganzer; Nikolaus Heinrich; Klaus-Robert Müller
Journal: J Comput Aided Mol Des Date: 2007-12-01 Impact factor: 3.686

2. Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

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5. Evaluation of log P, pK_a, and log D predictions from the SAMPL7 blind challenge.

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Journal: J Comput Aided Mol Des Date: 2021-06-24 Impact factor: 3.686