dnbaker/bioseq
Tokenizers and Machine Learning Models for biological sequence data
This tool helps biologists and biochemists prepare DNA or protein sequence data for machine learning models. You provide raw biological sequences, and it quickly converts them into numerical 'tokens' or 'one-hot encodings' that deep learning models can understand. Researchers working with genetic or protein data in fields like drug discovery, bioinformatics, or genomics would use this to build predictive models.
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Use this if you need to rapidly convert large datasets of DNA or protein sequences into a numerical format for training machine learning models, especially deep learning architectures like Transformers, CNNs, or LSTMs.
Not ideal if you need to work with highly specialized or non-standard biological sequence types beyond DNA or common protein alphabets, or if your primary need is not machine learning model input.
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25
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4
Language
C++
License
—
Category
Last pushed
Sep 27, 2024
Commits (30d)
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curl "https://pt-edge.onrender.com/api/v1/quality/transformers/dnbaker/bioseq"
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