AI in Drug Discovery

This open Access book constitutes the refereed proceedings of the First International Workshop on AI in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. The 12 papers presented her...

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Detalles Bibliográficos
Publicado en:Lecture Notes in Computer Science
Autores Corporativos: Clevert, Djork-Arné, Wand, Michael, Malinovská, Kristína, Schmidhuber, Jürgen, Tetko, Igor V.
Formato: Livro
Lenguaje:Inglês
Publicado: Springer Nature 2025
Materias:
Synthesis planning
chemo-informatics
big data
deep learning
drug discovery
convolution neural networks toxicity
GNNs
transformers
explainable AI
active learning
feature decomposition
de novo molecular design
quantum-mechanical properties
solvent effects
molecular property prediction
convergent routes
equivariant graph neural networks
structure-based drug discovery
constraints
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems
thema EDItEUR::P Mathematics and Science::PN Chemistry::PNR Physical chemistry::PNRA Computational chemistry
Acceso en línea:https://directory.doabooks.org/handle/20.500.12854/146360
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