Supplementary Materials from: AutoEpiCollect 2.0: Personalized Peptide Vaccine Design Using Machine Learning-Driven Genomic Analysis with Case Studies in Cervical Squamous Cell and Breast Carcinomas

This record contains the Supplementary Materials for AutoEpiCollect 2.0: Personalized Peptide Vaccine Design Using Machine Learning-Driven Genomic Analysis with Case Studies in Cervical Squamous Cell and Breast Carcinomas. It includes Excel, text, and PDB files generated from two case studies that demonstrate the use of AutoEpiCollect 2.0 to design personalized cancer vaccines. These files provide detailed outputs from the genomic analysis, peptide prediction, and peptide-MHC complex modeling used in the study.