Welcome to maxsmi’s documentation!

SMILES augmentation for deep learning based molecular property and activity prediction

Given a compound represented by its canonical SMILES, the Maxsmi model produces a prediction for each of the SMILES variations. The aggregation of these values leads to a per compound prediction and the standard deviation to an uncertainty in the prediction. The figure is taken from Kimber et al. (2021).

Contents:

• Getting Started
  • Installation
  • Citation
• User prediction
• SMILES augmentation
  • Canonical SMILES
  • Random SMILES
• Augmentation strategies
  • No augmentation
  • Augmentation with duplication
  • Augmentation without duplication
  • Augmentation with reduced duplication
  • Augmentation with estimated maximum
• Deep Neural Network Input
  • Example of one-hot encoded SMILES
• Data

Indices and tables

• Index

• Module Index

• Search Page