KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images

KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images

Abstract The application of convolutional neural networks (ConvNets) to harness high-content screening images or 2D compound representations is gaining increasing attention in drug discovery. However, existing applications often require large data sets for training, or sophisticated pretraining sche...

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Bibliographic Details
Main Authors: Isidro Cortés-Ciriano, Andreas Bender
Format: Article
Language:English
Published: BMC 2019-06-01
Series:Journal of Cheminformatics
Subjects:
Convolutional Neural Networks
Deep learning
Drug discovery
Bioactivity modelling
Random Forest
Cytotoxicity
Online Access:http://link.springer.com/article/10.1186/s13321-019-0364-5

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http://link.springer.com/article/10.1186/s13321-019-0364-5

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