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Fig 1.

The workflow of the identification of significant MeSH terms.

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Table 1.

Identification of significant DDI-related compounds and proteins from MeSH terms.

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Fig 2.

ROC curves for predicting DDI-related drug terms for cyclosporine, rifampin and theophylline.

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Fig 3.

ROC curves for predicting DDI-related protein terms for cyclosporine, rifampin and theophylline.

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Fig 4.

Protein-drug co-occurrence heatmaps for cyclosporine, rifampin and theophylline.

The rows and columns represent drug and protein terms respectively, and each cell is the normalized count of co-occurrences of the two terms. The normalized count can be calculated as normalized count = count/ total row count.

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Fig 5.

Phenomena-drug co-occurrence heatmaps for cyclosporine, rifampin and theophylline.

The rows and columns represent drug and phenomena terms respectively, and each cell is the normalized count of co-occurrences of the two terms. The normalized count can be calculated as normalized count = count/ total row count.

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Fig 5 Expand

Fig 6.

The social network of drug, proteins, phenomena and DDI types for three drug pairs, (A) cyclosporine-itraconazole, (B) rifampin-quindine, and (C) theophylline-omeprazole.

Drugs, proteins, phenomena and DDI types are shown in red, blue, green and orange, respectively.

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Fig 6 Expand