Method for finding universal peptide linkers

A method for finding universal peptide linkers, comprising:

• aligning peptides from a database back to a protein sequence, then increasing a required length of a flanking linker protein to generate positive samples;
• determining non-cutting point positions outside peptide intervals as possible negative samples, and cutting possible negative sample intervals into same length as the positive samples;
• removing duplicates of the positive samples from negative samples after defining the positive samples and the negative samples;
• grouping the negative samples through a clustering algorithm based on a clustering feature comprising continuous numerical values of polarity, molecular volume, hydrophobicity, and conformational entropy, and determining a quantity of clusters by an elbow method;
• calculating a difference or a distance between the positive samples and the negative samples using a group center or an average within each group;
• calculating a weighted average ranking based on an average distance ranking and a proportion ranking as a selection of peptide linkers;
• and
• connecting tumor neoantigens using the peptide linkers to manufacture a personalized cancer vaccine.