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Table 4 Similarity measures sorted by area under the ROC curve (AUC)

From: How can functional annotations be derived from profiles of phenotypic annotations?

Measure

AUC

Protein interactions

p-value

Resnik in CMPO

0.56

24

0.0102

Schlicker in CMPO

0.56

12

0.7512

Lin in CMPO

0.55

11

0.8332

Cohen’s kappa

0.54

27

0.0015

Pesquita in CMPO

0.54

14

0.5494

Jiang in CMPO

0.54

11

0.8332

TF-IDF

0.53

25

0.0055

Euclidean

0.53

16

0.3433

correlation

0.52

22

0.0311

Hamming

0.52

21

0.0513

cosine

0.49

13

0.6545

Jaccard

0.49

13

0.6545

Euclidean (logistic PCA)

0.46

25

0.0055

correlation (logistic PCA)

0.45

19

0.1242

Cosine (logistic PCA)

0.45

14

0.5494

  1. The second column represents the number of nearest neighbour gene pairs who are also protein interaction partners, and the third one, the p-values (computed from the hypergeometric distribution) that the number of observed interacting pairs is due to chance