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Reference | CI techniques | Performance | Datasets |
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[118] | Markov random field | Specificity: 45%, sensitivity: 64% | Functional probability of each protein |
[119] | Network flow based algorithm | Accuracy: 10–90% | Structure of protein interactive maps |
[120] | Neighbor based techniques | Precision: 0.9-1.0, recall: 98% | Label 1 and label 2 neighbors |
[121] | Association analysis based method | Accuracy: 93% | H confidence, adjacency matrix |
[122] | Naïve Bayes classifier | Precision: 49%, recall: 62%, MCC: 0.37 | PPI data |
[123] | RWR with -NN | Accuracy: 58–73% | Neighborhood features |
[124] | Time sequenced subnetwork | Significant module: 95.95% | Integrating the gene expression data and PPI data |
[125] | Gibbs sampling based bootstrapping | TP/FP: 0.5 to 1.5 | Interaction and annotation data |
[126] | Network based approach | Precision: 54.83%, -score: 43.74% | Function-function correlation |
[127] | Neighborhood majority voting system | Precision: 67.3%, recall: 40.30% | Diffusion state distance (DSD) |
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