shenwanxiang/bidd-molmap
MolMapNet: An Efficient ConvNet with Knowledge-based Molecular Represenations for Molecular Deep Learning
This project helps medicinal chemists and computational chemists evaluate how well a molecule will perform for a specific task, such as solubility or toxicity. You provide the chemical structure (SMILES string), and it transforms the molecular features into a standardized image-like representation. This 'MolMap' image can then be used to predict properties, helping you quickly assess new compounds.
145 stars.
Use this if you are a medicinal chemist or computational chemist who needs to predict molecular properties for drug discovery, material science, or toxicology, using an image-based deep learning approach.
Not ideal if you prefer traditional machine learning models without converting molecules to image-like representations, or if you primarily work with very large proteins.
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145
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34
Language
Jupyter Notebook
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Last pushed
Oct 26, 2025
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