Projects in Awesome Lists by PaccMann
A curated list of projects in awesome lists by PaccMann .
https://github.com/paccmann/chemical_representation_learning_for_toxicity_prediction
Chemical representation learning paper in Digital Discovery
chemoinformatics deep-learning property-prediction pytorch qsar toxicity-prediction
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_predictor
PyTorch implementation of bimodal neural networks for drug-cell (pharmarcogenomics) and drug-protein (proteochemometrics) interaction prediction
deep-learning drug-interaction drug-sensitivity pharmacogenomics proteochemometrics pytorch
Last synced: 11 Feb 2025
https://github.com/paccmann/paccmann_proteomics
PaccMann models for protein language modeling
protein-language-model pytorch transformer
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_kinase_binding_residues
Comparison of active site and full kinase sequences for drug-target affinity prediction and molecular generation. Full paper: https://pubs.acs.org/doi/10.1021/acs.jcim.1c00889
active-sites kinases knn machine-learning protein-ligand-interactions proteochemometrics
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_rl
Code pipeline for the PaccMann^RL in iScience: https://www.cell.com/iscience/fulltext/S2589-0042(21)00237-6
de-novo-drug-design deep-learning drug-discovery drug-sensitivity generative-models transcriptomics
Last synced: 28 Mar 2025
https://github.com/paccmann/titan
Code for "T Cell Receptor Specificity Prediction with Bimodal Attention Networks" (https://doi.org/10.1093/bioinformatics/btab294, ISMB 2021)
compound-protein-interaction deep-learning immunology protein-ligand tcr-epitope
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_datasets
pytoda - PaccMann PyTorch Dataset Classes. Read the docs: https://paccmann.github.io/paccmann_datasets/
bioinformatics chemoinformatics deep-learning python pytorch rdkit smiles
Last synced: 09 Apr 2025
https://github.com/paccmann/paccmann_sarscov2
Code for paper on automation of discovery and synthesis of targeted molecules: https://iopscience.iop.org/article/10.1088/2632-2153/abe808
accelerated-discovery computer-aided-synthesis-planning de-novo-drug-design deep-learning drug-discovery proteochemometrics sars-cov-2
Last synced: 28 Mar 2025
https://github.com/paccmann/fdsa
A fully differentiable set autoencoder
deep-learning multimodal-data set-autoencoder
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_chemistry
Generative models of chemical data for PaccMann^RL
deep-learning drug-discovery generative-model molecule-generation vae
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_generator
Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).
deep-reinforcement-learning drug-discovery generative-model molecule-generation vae
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_gp
PyTorch/skopt based implementation of Bayesian optimization with Gaussian processes - build to optimize latent spaces of VAEs to generate molecules with desired properties
bayesian-optimization chemoinformatics gaussian-processes generative-model machine-learning
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_omics
Generative models for transcriptomics profiles and proteins
deep-learning generative-model proteomics transcriptomics vae variational-autoencoder
Last synced: 10 Apr 2025
https://github.com/paccmann/paccmann_polymer
Graph-regularized VAE and the impact of topology on learned representations
deep-learning gnn graph-regularized-vae manifold-learning pytorch vae
Last synced: 28 Mar 2025
https://github.com/paccmann/reinvent_models
PaccMann fork of Reinvent Models
Last synced: 28 Mar 2025