modlab (Computer-Assisted Drug Design group ETH Zürich)

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

BIMODAL. Supporting code for the paper "Bidirectional Molecule Generation with Recurrent Neural Networks" (J. Chem. Inf. 2020, 60, 3).

dragonfly_gen. De novo drug design with deep interactome learning

molecular_design_with_beam_search. Jupyter Notebook

lsfml. Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning

de_novo_design_RNN. Code for "De novo molecular design with chemical language models"

molgrad. Coloring molecules with explainable artificial intelligence

hybridCLMs. Supporting code for the paper «Leveraging molecular structure and bioactivity with chemical language models for drug design»

whales_descriptors. python code for calculating the WHALES (Weighted Holistic Atom Localization and Entity Shape) molecular descriptors

LSTM_peptides. Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.

modlAMP. Python package for peptide sequence generation, peptide descriptor calculation and sequence analysis.