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Jiang et al., 2021 - Google Patents

Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein–ligand interaction predictions

Jiang et al., 2021

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Document ID
5838776965385238772
Author
Jiang D
Hsieh C
Wu Z
Kang Y
Wang J
Wang E
Liao B
Shen C
Xu L
Wu J
Cao D
Hou T
Publication year
Publication venue
Journal of medicinal chemistry

External Links

Snippet

Accurate quantification of protein–ligand interactions remains a key challenge to structure- based drug design. However, traditional machine learning (ML)-based methods based on handcrafted descriptors, one-dimensional protein sequences, and/or two-dimensional graph …
Continue reading at www.researchgate.net (PDF) (other versions)

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    • G06F19/16Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
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