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paccmann_generator

imported

therapeutics/paccmann-generator

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

Machine-generated from the listed sources and not yet reviewed by a human.

paccmann_generator project image
GitHub preview card for PaccMann/paccmann_generator. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Therapeutics
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
PaccMann
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
deep-reinforcement-learning · drug-discovery · generative-model · molecule-generation · vae
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • paccmann_chemistrydrug-discovery · generative-model · molecule-generation · vae

    Generative models of chemical data for PaccMann^RL

  • molgendrug-discovery · generative-model · vae

    Lightweight toolkit for de novo molecular generation: SMILES & SELFIES tokenizers, CharRNN / MolGPT / VAE models, training, sampling, and MOSES-style metrics.

  • BBARdrug-discovery · generative-model · molecule-generation

    Official Github for "Molecular generative model via retrosynthetically prepared chemical building block assembly" (Advanced Science)

  • paccmann_omicsgenerative-model · vae

    Generative models for transcriptomics profiles and proteins

  • BInDdrug-discovery · molecule-generation

    Official implementation of "BInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design" (Advanced Science)

  • GeoLDMdrug-discovery · molecule-generation

    Geometric Latent Diffusion Models for 3D Molecule Generation

sources
  1. api.github.com/repos/PaccMann/paccmann_generator
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2024-05-22, 11 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/6.json→ .entries["paccmann-generator"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.