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Table 3 Co-citer analysis of top 30 breast cancer driver genes identified by our method

From: Identifying driver genes involving gene dysregulated expression, tissue-specific expression and gene-gene network

GenesCancerBreastDriveris driverDyTidriverDiffusionDriverNetDawnRankMuf maxMuf sum
TP5367721356110112331272
PIK3CA119933454121562123
MAP 3 K11356221312818489928
GATA31541228148513688817
CDH1141035819154241016
ERBB2533543327816726490873
UBC134302072403122221
NCOR1109453181391248668
ASH1L401091097NA19861846729
PIK3R113121711016010261345
EP3002698641116851783674
DYNC1H1922012638171017107
HUWE1294301325128459112
PTEN30476726411418598193379
MAP 3 K132011156189NA330326542045
NF1165241111614141194144
TTN10120172581657175
TPP24020181041NA267431722926
UFL1711019802NANA34933129
BRCA146524017221202511NA36127
BACH28120218101182236622981079
JAK2382921912211832NA73119
ERBB335417841237329810207
ERBB43502204124745627618410
MAP 2 K470102125127342389886
CTCF632131265520211102729
PRKCB4191127174593180151
SASH113810281011NANA37064179
TAF11031129225863335919
SPTA130103021217251018109
  1. The second to the fourth column show the co-appeared times of top 30 identified genes with ‘driver’, ‘breast’ and ‘cancer’ (from the left to the right). is_driver indicates whether the given gene is a driver or not in the benchmark dataset. The left columns represent the ranking positions of identified genes in Dytidriver, Diffusion, DriverNet, DawnRank, Muf_max, Muf_sum respectively