Release Notes

v0.11.1 July 2023

  • This package is built using OpenEye-orionplatform==5.1.0, OpenEye-toolkits==2023.1.0, and OpenEye-Snowball==0.26.0.

  • All Floes have new brief texts and Floe categories.

Feature Updates

  • Keras Hyperparameter Tuner.

    • This is an optimizer for fingerprint based model building (classification and regression).

    • Choose from Hyperband, RandomSearch, and Bayesian Optimization.

    • It is available in Floes: ML Build: Regression Model with Tuner using Fingerprints for Small Molecules and ML Build: Classification Model with Tuner using Fingerprints for Small Molecules.

  • This release includes a new style for Floe reports, bug fixes, and more stable Floe runs for larger data.

New Floes in this package

v0.10.5 March 2023

Feature Updates

  • This is the first minor release of Model Building package with package version 0.10.4.

  • This package is built using OpenEye-orionplatform==4.4.0, OpenEye-toolkits==2022.2.1, and OpenEye-Snowball==0.24.0..

  • Added Overfit correlation and coefficients [refer to Optimization Strategy V] to train models without overfit.

  • Added Precision, Recall, Specificity, and Sensitivity parameters in floe report for Classification Model Building Floes. These fields are also available in record output.

v0.10.0 December 2022

Feature Updates

  • This is the second major release of Model Building package with package version 0.10.0.

  • This package is built using OpenEye-orionplatform==4.5.4, OpenEye-toolkits==2022.2.1, and OpenEye-Snowball==0.24.0..

  • All floes have a new brief parameter and floe categories.

New Floes in this package

Old Floes in this package

  • ML Regression Model Building using Fingerprints for Small Molecules (previously Neural Network Based Regression Model Building) trains multiple Neural Network (Full or Probabilistic) Regression models on physical properties of small molecules. Uses cheminformatics and machine learning to train said models.

  • ML Regression using Fingerprints for Small Molecules (previously Physical Property Prediction for Small Molecules using Machine Learning) predicts property from a pretrained neural network model. Needs molecule database and neural network model dataset as input (trained using the previous floe).

  • Solubility Prediction for Small Molecules using Machine Learning and Cheminfo Fingerprints predicts solubility in log uM using neural network based machine learning. Needs molecule database as input.

v0.9.2 September 2022

Minor Bug Fixes

  • This package is built using OpenEye-orionplatform==4.4.0, OpenEye-toolkits==2022.1.1, and OpenEye-Snowball==0.24.0..

  • Bug fixed on Physical Property Prediction for Small Molecules using Machine Learning

  • Model and Record ID in Neural Network Based Regression Model Building renamed for user convenience.

  • Better use case handling for wrong inputs.

  • Frequently Asked Questions section added

v0.9.0 July 2022

General Notice

  • This is the first release of Model Building package with package version 0.9.0.

  • This package is built using OpenEye-orionplatform==4.4.0, OpenEye-toolkits==2022.1.1, and OpenEye-Snowball==0.24.0..

  • All floes have a new brief parameter and floe categories.

Floes in this package

  • Neural Network Based Regression Model Building trains multiple Neural Network (Full or Probabilistic) Regression models on physical properties of small molecules. Uses cheminformatics and machine learning to train said models.

  • Physical Property Prediction for Small Molecules using Machine Learning predicts property from a pretrained neural network model. Needs molecule database and neural network model dataset as input (trained using the previous floe).

  • Solubility Prediction for Small Molecules using Machine Learning and Cheminfo Fingerprints predicts solubility in log uM using neural network based machine learning. Needs molecule database as input.