BioinformaticsbioRxivPreprint
PepMSND: Integrating Multi-level Feature Engineering and Comprehensive Databases to Enhance in vivo/in vitro Peptide Blood Stability Prediction
Hu Haomeng, Chengyun Zhang, Zhenyu Xu, Hongliang Duan
The paper develops a deep learning model called PepMSND to predict peptide blood stability using multi-level feature engineering and a comprehensive database of 635 samples, achieving high accuracy and AUC.
DOI 10.1101/2024.12.12.628290