title: Prediction of 1-octanol solubilities using data from the Open Notebook Science Challenge.
abstract: BACKGROUND
  1-Octanol solubility is important in a variety of applications involving pharmacology and environmental chemistry. Current models are linear in nature and often require foreknowledge of either melting point or aqueous solubility. Here we extend the range of applicability of 1-octanol solubility models by creating a random forest model that can predict 1-octanol solubilities directly from structure.
  
  
  RESULTS
  We created a random forest model using CDK descriptors that has an out-of-bag (OOB) R2value of 0.66 and an OOB mean squared error of 0.34. The model has been deployed for general use as a Shiny application.
  
  
  CONCLUSIONS
  The 1-octanol solubility model provides reasonably accurate predictions of the 1-octanol solubility of organic solutes directly from structure. The model was developed under Open Notebook Science conditions which makes it open, reproducible, and as useful as possible.Graphical abstract.
authors.affiliation: Department of Computing and Mathematics, Oral Roberts University, 7777 S. Lewis Avenue, Tulsa, OK 74171 USA.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Buonaiuto
authors.affiliation: Department of Computing and Mathematics, Oral Roberts University, 7777 S. Lewis Avenue, Tulsa, OK 74171 USA.
authors.forename: Andrew S I D
authors.initials: AS
authors.lastname: Lang
keywords: 1-Octanol solubility; Modeling; Open notebook science