Useful functions for working with small molecules

simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.

CReM: chemically reasonable mutations framework

Jupyter active learning annotator widget.

A collection of notebook to learn the Applied Predictive Modeling using Python.

ChEMBL database structure pipelines

add-on to plotly which show molecule images on mouseover!

Python package for graph neural networks in chemistry and biology

Robust representation of semantically constrained graphs, in particular for molecules in chemistry

Implementation of the method proposed in the paper "Efficient Multi-Objective Molecular Optimization in a Continuous Latent Space" by Robin Winter, Floriane Montanari, Andreas Steffen, Hans Briem, …

The source code for ADME@NCATS application that hosts prediction models for ADME properties. Link to application: https://opendata.ncats.nih.gov/adme/home

Deep learning toolkit for Drug Design with Pareto-based Multi-Objective optimization in Polypharmacology

PyTorch-based Neural Graph Fingerprint for Organic Molecule Representations

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

Supporting code for the paper «Generative molecular design in low data regimes»

ML models to convert molecules to ESI mass spectra and maybe back again

A library that integrates huggingface transformers with the world of fastai, giving fastai devs everything they need to train, evaluate, and deploy transformer specific models.

Please use fastbook's /clean folder instead of this

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

The fastai book, published as Jupyter Notebooks

Pharmacophore tool based on OpenEye toolkits