Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy

Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy

Abstract Background Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor rejection. Since it is impractical to exper...

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Bibliographic Details
Main Authors: Elham Sherafat, Jordan Force, Ion I. Măndoiu
Format: Article
Language:English
Published: BMC 2020-12-01
Series:BMC Bioinformatics
Subjects:
Machine learning
Positive-unlabeled learning
Somatic variant calling
Peptide identification
Exome sequencing
Tandem mass-spectrometry
Online Access:https://doi.org/10.1186/s12859-020-03813-x

Internet

https://doi.org/10.1186/s12859-020-03813-x

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