PaccMann

PyTorch/skopt based implementation of Bayesian optimization with Gaussian processes - build to optimize latent spaces of VAEs to generate molecules with desired properties

PyTorch implementation of bimodal neural networks for drug-cell (pharmarcogenomics) and drug-protein (proteochemometrics) interaction prediction

pytoda - PaccMann PyTorch Dataset Classes. Read the docs: https://paccmann.github.io/paccmann_datasets/

Code for "T Cell Receptor Specificity Prediction with Bimodal Attention Networks" (https://doi.org/10.1093/bioinformatics/btab294, ISMB 2021)

Chemical representation learning paper in Digital Discovery

Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).

PaccMann website

A fully differentiable set autoencoder

Generative models of chemical data for PaccMann^RL