Comparison of Target Features for Predicting Drug-Target Interactions by Deep Neural Network Based on Large-Scale Drug-Induced Transcriptome Data

Uncovering drug-target interactions (DTIs) is pivotal to understand drug mode-of-action (MoA), avoid adverse drug reaction (ADR), and seek opportunities for drug repositioning (DR). For decades, in silico predictions for DTIs have largely depended on structural information of both targets and compou...

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Detalles Bibliográficos
Autores principales: Lee, Hanbi, Kim, Wankyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723794/
https://www.ncbi.nlm.nih.gov/pubmed/31382356
http://dx.doi.org/10.3390/pharmaceutics11080377

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723794/
https://www.ncbi.nlm.nih.gov/pubmed/31382356
http://dx.doi.org/10.3390/pharmaceutics11080377

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