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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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| Publicado no: | BMC Bioinformatics |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8056558/ https://ncbi.nlm.nih.gov/pubmed/33879050 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-021-04127-2 |
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