Development and evaluation of a deep learning model for protein–ligand binding affinity prediction | Zendy

Marta M. Stepniewska-Dziubinska | Zendy; Piotr Zielenkiewicz | Zendy; Paweł Siedlecki | Zendy

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Development and evaluation of a deep learning model for protein–ligand binding affinity prediction

Author(s) -

Marta M. Stepniewska-Dziubinska,

Piotr Zielenkiewicz,

Paweł Siedlecki

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty374

Subject(s) - computer science , benchmark (surveying) , deep learning , artificial intelligence , drug discovery , machine learning , process (computing) , set (abstract data type) , feature (linguistics) , task (project management) , data mining , bioinformatics , engineering , geodesy , biology , programming language , geography , operating system , systems engineering , linguistics , philosophy

Structure based ligand discovery is one of the most successful approaches for augmenting the drug discovery process. Currently, there is a notable shift towards machine learning (ML) methodologies to aid such procedures. Deep learning has recently gained considerable attention as it allows the model to 'learn' to extract features that are relevant for the task at hand.

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