Cargando…
Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy
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 experimentall...
Autores principales: | Sherafat, Elham, Force, Jordan, Măndoiu, Ion I. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772914/ https://www.ncbi.nlm.nih.gov/pubmed/33375939 http://dx.doi.org/10.1186/s12859-020-03813-x |
Ejemplares similares
-
Semi-supervised peak calling with SPAN and JBR genome browser
por: Shpynov, Oleg, et al.
Publicado: (2021) -
Semi-supervised machine learning for automated species identification by collagen peptide mass fingerprinting
por: Gu, Muxin, et al.
Publicado: (2018) -
Person re-identification via semi-supervised adaptive graph embedding
por: Liu, Jiao, et al.
Publicado: (2022) -
Semi-supervised learning /
Publicado: (2010) -
Halvade somatic: Somatic variant calling with Apache Spark
por: Decap, Dries, et al.
Publicado: (2022)