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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]