Abstract: Disclosed are a system and a method of predicting neoantigens and immune response induction. The system and the method may verify induction of immunity against neoantigens having high binding affinity by identifying neoantigen candidates through genomic mutations and then predicting the binding affinities of the neoantigen candidates for MHC through molecular dynamics. The method provides neoantigen immunotherapy information for identifying a neoantigen using artificial intelligence (AI)-based molecular dynamics big data, and includes steps of: (A) identifying neoantigen candidates through a genomic mutation; (B) filtering the specificities of the neoantigen candidates for tissue and disease; (C) predicting the in silico binding of the neoantigens to MHC; and (D) calculating and ranking TCR activity.

Abstract: Disclosed is a human haplotyping method. The method includes: collecting a sequence of a gene to be analyzed; matching and aligning reads of the collected sequence to a reference stored in a database; electing candidate alleles from among alleles of the reference; and selecting a final allele from among the candidate alleles.

Abstract: Disclosed is a human haplotyping method. The method includes: collecting a sequence of a gene to be analyzed; matching and aligning reads of the collected sequence to a reference stored in a database; electing candidate alleles from among alleles of the reference; and selecting a final allele from among the candidate alleles.