Table 1 Top ten targets that consistently appear in the top positive or negative interactions.

From: Machine learning identifies candidates for drug repurposing in Alzheimer’s disease

Symbol

Direction

n

p

padj

NEK6

Positive

257

8.25E−129

1.32E−06

NEK3

Positive

237

5.45E−71

2.52E−04

RPS6KA2

Positive

246

7.62E−68

4.80E−04

LATS2

Positive

280

3.82E−60

9.53E−04

ABL2

Negative

204

2.88E−51

9.94E−04

DCLK3

Positive

250

1.23E−56

1.24E−03

MARK1

Positive

271

4.12E−52

1.92E−03

STK17B

Positive

264

1.22E−49

2.21E−03

NEK9

Positive

295

5.14E−50

2.66E−03

STK17A

Positive

202

8.57E−37

3.23E−03

  1. The table lists targets (symbol), whether those pairs are primarily positive or negative interactions (direction), the number of pairs they appear in (n), and the overall p-value computed by aggregating p-values from individual Wilcoxon Rank Sum tests (Fig. 5b) using the Brown’s method. Additional adjustment for multiple hypothesis testing was performed using the Benjamini Hochberg method (padj).
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