Prediction of peptide hormones using an ensemble of machine learning and similarity-based methods
Dashleen Kaur, Akanksha Arora, Palani Vigneshwar, Gajendra P. S. Raghava
The paper develops a hybrid model combining machine learning and similarity-based methods to predict hormonal peptides, achieving high accuracy on a dataset from plants and animals.