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The study explores the hypothesis that bioactive peptides share general features across diverse classes, leading to the development of a novel predictor called PeptideRanker. This predictor, trained on various peptide databases, demonstrated predictive power comparable to or better than existing specific predictors for different peptide classes. The findings suggest that computational methods can enhance the discovery and design of bioactive peptides by identifying common characteristics across functional c
- Author
- Juliana Lima
- Language
- EN