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Table 7 Best-Predicted Proteins using Random Forest

From: Challenges in proteogenomics: a comparison of analysis methods with the case study of the DREAM proteogenomics sub-challenge

CombinedBRCAOVA
Protein NameCountProtein NameCountProtein NameCount
MAP 1B6ERAP26ASRGL16
PSIP16GRB76LAP36
ACADSB5PACSIN25GMPR5
ANPEP5SSH35ICAM15
ASRGL15ERBB24MAP 1B5
CMBL5ESR14MSN5
DDX585IFIT54VCP5
FAM129A5NCAPH4WARS5
HMGCL5PPFIA14XPO55
OXCT15PRODH4ASS14
  1. The list of proteins whose predictions are most frequently found to have one of the top 100 correlation values to ground truth across 10 cross-validations. These predictions are generated using the random forests model