ChemScreener: an active learning enabled hit discovery workflow with WDR5 inhibitor case study
Abstract Active deep learning offers a promising approach for hit discovery starting from limited data by iteratively updating and improving models during screening by applying new data and adapting decisions. Key open questions include how best to explore chemical space, how it compares to non-iter...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , , , , , |
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| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
BMC
2026-04-01
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| Σειρά: | Journal of Cheminformatics |
| Θέματα: | |
| Διαθέσιμο Online: | https://doi.org/10.1186/s13321-026-01204-7 |
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