Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models
Journal article, 2023
Learning algorithms
Convolutional neural networks
Deep learning
Solubility prediction
Molecules
Author
Jonathan G.M. Conn
University of Strathclyde
James W. Carter
University of Strathclyde
Justin J.A. Conn
University of Strathclyde
Vigneshwari Subramanian
AstraZeneca AB
Andrew Baxter
GlaxoSmithKline
Ola Engkvist
Chalmers, Computer Science and Engineering (Chalmers)
AstraZeneca AB
Antonio Llinas
AstraZeneca AB
Ekaterina L. Ratkova
AstraZeneca AB
Stephen D. Pickett
GlaxoSmithKline
James L. Mcdonagh
IBM Research Europe
David S. Palmer
University of Strathclyde
Journal of Chemical Information and Modeling
1549-9596 (ISSN) 1549960x (eISSN)
Vol. 63 4 1099-1113Subject Categories
Other Computer and Information Science
Bioinformatics (Computational Biology)
Bioinformatics and Systems Biology
DOI
10.1021/acs.jcim.2c01189
PubMed
36758178
Related datasets
Blinded Predictions and Post-hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models [dataset]
DOI: 10.5281/zenodo.7130064