We are pleased to announce the release of jp²rt, a Java and Python package to Predict Retention Time, from NAICONS Srl laboratories. The package is available on GitHub.
It represents a modern reimplementation of the Retip application. Retip is a tool designed to predict the retention time of compounds based on their molecular structure. It employs machine learning regression models trained on molecular descriptors derived from a small set of compounds with experimentally determined retention times. jp²rt enhances feature computation efficiency using a Java parallel implementation and replaces the previous R-based machine learning code with a modern Python-based stack.
Key components include:
📌 jp²rt Java package: Enables rapid and reliable computation of molecular descriptors using the Chemistry Development Kit.
📌 jp²rt Python package: Facilitates model training and prediction using the scikit-learn machine learning library.
✨ For those using machine learning to predict retention times of small molecules within chromatographic analyses, we are sure this will speed up the process!