Improved prediction of anti-angiogenic peptides based on machine learning models and comprehensive features from peptide sequences
Abstract Angiogenesis is a key process for the proliferation and metastatic spread of cancer cells. Anti-angiogenic peptides (AAPs), with the capability of inhibiting angiogenesis, are promising candidates in cancer treatment. We propose AAPL, a sequence-based predictor to identify AAPs with machine...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Portfolio
2024-06-01
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| Serie: | Scientific Reports |
| Accesso online: | https://doi.org/10.1038/s41598-024-65062-9 |
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