METHOD AND COMPUTER PROGRAM TO PREDICT NEOANTIGEN BY STANDARDIZING THE LENGTH OF PEPTIDES OF VARIOUS LENGTHS BY FOLDING

METHOD AND COMPUTER PROGRAM TO PREDICT NEOANTIGEN BY STANDARDIZING THE LENGTH OF PEPTIDES OF VARIOUS LENGTHS BY FOLDING

According to the present invention, disclosed is a method for processing a peptide sequence exceeding a unit length through a folding process in predicting a neoantigen by using the peptide sequence and HLA class I and/or II allele sequences. According to this, a peptide sequence included in a cance...

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Bibliographische Detailangaben
Hauptverfasser: OH SE JIN, PAIK SOON MYUNG, HONG SEONG EUI, HWANG TAE SOON
Format: Patent
Sprache:eng ; kor
Schlagworte:
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
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Beschreibung
Zusammenfassung:According to the present invention, disclosed is a method for processing a peptide sequence exceeding a unit length through a folding process in predicting a neoantigen by using the peptide sequence and HLA class I and/or II allele sequences. According to this, a peptide sequence included in a cancer tissue can determine a neoantigen in a cancer tissue regardless of diversity of lengths. Through this, it is possible to overcome imbalance and lack of information in learning data by a length and predict a binding force more accurately so as to determine a new antigen in a cancer tissue. 본 개시는 펩타이드 서열 및 HLA 클래스 I 및/또는 II 대립유전자 서열을 이용하여 신항원을 예측함에 있어서, 단위 길이를 초과하는 펩타이드 서열을 접힘의 과정으로 처리하는 방법을 개시한다. 이에 따르면, 암 조직에 포함된 펩타이드 서열은 길이의 다양성에 상관없이, 암 조직 내 신항원을 결정할 수 있다. 이를 통해 길이 별 학습데이터의 불균형 및 정보 부족을 극복하고 보다 정확한 결합력을 예측하여 암 조직 내 신항원을 결정할 수 있다.