AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders

BACKGROUND: Drug–target interaction (DTI) plays a vital role in drug discovery. Identifying drug–target interactions related to wet-lab experiments are costly, laborious, and time-consuming. Therefore, computational methods to predict drug–target interactions are an essential task in the drug discov...

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Detalles Bibliográficos
Autores principales: Sajadi, Seyedeh Zahra, Zare Chahooki, Mohammad Ali, Gharaghani, Sajjad, Abbasi, Karim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056558/
https://www.ncbi.nlm.nih.gov/pubmed/33879050
http://dx.doi.org/10.1186/s12859-021-04127-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056558/
https://www.ncbi.nlm.nih.gov/pubmed/33879050
http://dx.doi.org/10.1186/s12859-021-04127-2

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