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Table 3 Best-Predicted Proteins using Bayesian Networks

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

Combined

BRCA

OVA

Protein Name

Count

Protein Name

Count

Protein Name

Count

CMBL

9

BCAN

9

CBX2

9

WFDC2

8

MAEL

9

GFOD2

9

SERPINB3

8

MAGEC1

9

GP1BA

9

NUCB2

8

TESC

9

SERPINB3

8

MAGEA9

8

WIPF3

9

SLC35B1

8

FDXR

8

CD1A

8

CRADD

7

SFX2

7

HLA-DQB2

8

CYP11A1

7

RABEP1

7

AKR1B15

7

MINDY2

7

MYH14

7

CST4

7

MMP10

7

ALCAM

7

CYP4F22

7

CALB1

6

  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 Bayesian network model