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Table 2 Summary of the assessment result for different network construction methods on the time-series gene expression data

From: Integrating external biological knowledge in the construction of regulatory networks from time-series expression data

Method Data used Network size p-value of chi sq testa TPR (%)b # mis-class.c TP O/Ed
iBMA-prior Gene expression + external data 21951 <1.00E-320 18.00 19282 593 4.11
iBMA-shortlist Gene expression + external data 67440 <1.00E-320 12.78 24673 1287 2.92
Network A from Yeung et al. Gene expression + external data 65122 1.68E-111 9.98 22485 662 2.28
LASSO-shortlist Gene expression + external data 255293 <1.00E-320 11.07 46482 4169 2.53
LAR-shortlist Gene expression + external data 242495 <1.00E-320 11.28 44765 4017 2.57
iBMA-size Gene expression data only 17202 5.75E-56 16.84 17622 114 3.84
iBMA-noprior Gene expression data only 63026 1.75E-23 8.85 18903 186 2.02
LASSO-noprior Gene expression data only 564321 2.56E-10 5.20 38399 1231 1.19
LAR-noprior Gene expression data only 194687 1.38E-40 7.71 22777 511 1.76
  1. a The p-value of Pearson’s chi-square test measures the strength of association between an inferred network and the Yeastract database.
  2. b True positive rate (TPR) is defined as the proportion of inferred regulatory relationships that are documented in Yeastract.
  3. c The number of misclassified cases is the sum of false positives and false negatives.
  4. d The O/E ratio is the number of folds the observed number of recovered relationships (i.e., TP) in excess of the expected count of recovery by chance.
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BMC Systems Biology

ISSN: 1752-0509

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