A comparison of embedding aggregation strategies in drug–target interaction prediction
Abstract The prediction of interactions between novel drugs and biological targets is a vital step in the early stage of the drug discovery pipeline. Many deep learning approaches have been proposed over the last decade, with a substantial fraction of them sharing the same underlying two-branch arch...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-02-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-024-05684-y |