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A Method of Optimizing Weight Allocation in Data Integration Based on Q-Learning for Drug-Target Interaction Prediction
Calculating and predicting drug-target interactions (DTIs) is a crucial step in the field of novel drug discovery. Nowadays, many models have improved the prediction performance of DTIs by fusing heterogeneous information, such as drug chemical structure and target protein sequence and so on. Howeve...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959213/ https://www.ncbi.nlm.nih.gov/pubmed/35356288 http://dx.doi.org/10.3389/fcell.2022.794413 |