paccmann_omics
importedsoftware/paccmann-omics
Generative models for transcriptomics profiles and proteins
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- PaccMann
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/PaccMann/paccmann_omics
- Documentation
- unknown
- Tags
- deep-learning · generative-model · proteomics · transcriptomics · vae · variational-autoencoder
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- molgengenerative-model · vae
Lightweight toolkit for de novo molecular generation: SMILES & SELFIES tokenizers, CharRNN / MolGPT / VAE models, training, sampling, and MOSES-style metrics.
- paccmann_chemistrygenerative-model · vae
Generative models of chemical data for PaccMann^RL
- paccmann_generatorgenerative-model · vae
Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).
- scgengenerative-model · transcriptomics
Single cell perturbation prediction
- 3d_very_deep_vaevariational-autoencoder
PyTorch implementations of variational autoencoders for 3D images
- ecgxaivariational-autoencoder
Neatly packaged AI methods for explainable ECG analysis
- api.github.com/repos/PaccMann/paccmann_omicsretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2021-09-17, 7 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 →
/v1/entries/18.json→ .entries["paccmann-omics"]
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