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Table 3 The enrichment rate of driver genes predicted by EARN. (a) MBCA, (b) BRCA

From: EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

All different cancers Metastatic breast cancer
HCMDB HCMDB
PGEMCH
(#)
RGMHP
(#)
PGEMCH
(%)
PGEMBCH (#) RGMBHP
(#)
PGEMBCH
(%)
(a) MBCA      
 292 2203 13.25 73a 585 12.48
All different cancers Breast cancer
OMIM, CGC, and NCG OMIM, CGC, and NCG
PKGECC
(#)
RKGCPP
(#)
PKGECC
(%)
PKGEBC
(#)
RKGBPP
(#)
PKGEBC
(%)
(b) BRCA      
 1398 2403 58.18 145 201 72.14
  1. PGEMCH, predicted genes by EC associated with different metastatic cancers that are confirmed in HCMDB, RGMHP, remained genes related to different metastatic cancers in the HCMDB after excluding positive training set, PGEMBCH, predicted genes by EC associated with metastatic breast cancer that are confirmed in HCMDB, RGMBHP, remained genes related to metastatic breast cancer in the HCMDB after excluding positive training set, PKGECC, predicted known genes by EC associated with different cancers that are confirmed in OMIM, CGC, and NCG, RKGCPP, remained known genes related to different cancers in the public databases after excluding positive training set, PKGEBC, predicted known genes by EC associated with breast cancer that are confirmed in OMIM, CGC, and NCG, RKGBPP, remained known genes related to breast cancer in the public databases after excluding positive training set
  2. aThese 73 genes have been also cited in 108 studies of HCMDB [see Additional file 9: S42]