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Table 3 Prioritization with ProDiGe4 for 8 diseases with a large training set of known genes

From: ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

Disease name

MIM Id

Training set

Training ∩ IPA

Precision (%)

Recall (%)

P-value

Prostate cancer

176807

12

12

41

7.5

5.3e-40

Colorectal cancer

114500

17

17

51

5.7

7.3e-44

Diabetes mellitus

125853

26

22

21

1.4

2.1e-06

Alzheimer

104300

11

10

23

2.3

3.8e-11

Gastric cancer

137215

12

12

16

7.1

9.3e-16

Leukemia acute myeloid

601626

17

16

13

10.0

2.8e-15

Breast cancer

114480

19

16

33

3.7

6.4e-22

Schizophrenia

181500

17

11

6

3.2

4.5e-05

  1. The results were validated by comparing our top 100 genes with a list of genes related to the disease, extracted from Ingenuity database.
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BMC Bioinformatics

ISSN: 1471-2105

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