Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.
Elham SherafatJordan ForceIon I MăndoiuPublished in: BMC bioinformatics (2020)
Experimental results on real datasets demonstrate that PLATO has improved performance compared to model-based approaches for two key steps in TRMN prediction, namely somatic variant calling from exome sequencing data and peptide identification from MS/MS data.