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moleculegen-ml

imported

therapeutics/moleculegen-ml

Generate novel molecules using neural language models

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

moleculegen-ml project image
GitHub preview card for sanjaradylov/moleculegen-ml. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Therapeutics
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
cheminformatics · convolutional-neural-networks · drug-discovery · fine-tuning · language-model · machine-learning · mxnet · recurrent-neural-networks · transformers
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.

  • reinvent-randomizeddrug-discovery · recurrent-neural-networks

    Recurrent Neural Network using randomized SMILES strings to generate molecules

  • smiles-gptcheminformatics · drug-discovery · transformers

    Generative Pre-Training from Molecules

  • ai4science-studiodrug-discovery · fine-tuning

    How-to guides and AMD/ROCm optimization recipes for open AI-for-science models.

  • MediBeng-Whisper-Tinyfine-tuning · transformers

    MediBeng Whisper Tiny improves doctor-patient transcription by training the Whisper Tiny model to translate mixed Bengali-English speech into English, making it easier for analysis, record-keeping,…

  • EEGLearnconvolutional-neural-networks · recurrent-neural-networks

    A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

  • gninacheminformatics · convolutional-neural-networks · drug-discovery

    A deep learning framework for molecular docking

sources
  1. api.github.com/repos/sanjaradylov/moleculegen-ml
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2022-05-23, 5 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/25.json→ .entries["moleculegen-ml"]

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