Maxsmi: Maximizing molecular property prediction performance with confidence estimation using SMILES augmentation and deep learning

Maxsmi: Maximizing molecular property prediction performance with confidence estimation using SMILES augmentation and deep learning

Accurate molecular property or activity prediction is one of the main goals in computer-aided drug design. Quantitative structure-activity relationship (QSAR) modeling and machine learning, more recently deep learning, have become an integral part of this process. Such algorithms require lots of dat...

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Bibliographic Details
Main Authors: Talia B. Kimber, Maxime Gagnebin, Andrea Volkamer
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Artificial Intelligence in the Life Sciences
Subjects:
Deep learning
Molecular property prediction
Data augmentation
Open-source
Confidence assessment
SMILES
Online Access:http://www.sciencedirect.com/science/article/pii/S2667318521000143

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http://www.sciencedirect.com/science/article/pii/S2667318521000143

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