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Table 1 Example of a feature matrix generated from linked data

From: Learning from biomedical linked data to suggest valid pharmacogenes

ID Gene attribute Phenotype Drug attribute G-D link G-P link D-P link Class
PA7360-PA131301952 Signal transduction C0007131 L01XE2 Antagonist clinvar: so_0001575 sider: indication 1
PA7360-PA131301952 Immune system C0007131 L01XE2 Antagonist clinvar: so_0001575 sider: indication 1
PA7360-PA131301952 Signal transduction C0007131 L01XE2 Antagonist clinvar: so_0001619 sider: indication 1
PA7360-PA131301952 Immune system C0007131 L01XE2 Antagonist clinvar: so_0001519 sider: indication 1
  1. All the instances (e.g., lines) describe the same gene–drug relationships (EGFR–Gefitinib), which is associated in PharmGKB with a high level of evidence (Class=1). Figure 3 shows some of the data associated with this relationships in linked data. Values are extracted from the graph and are encoded in various manner. For example, values of phenotypes are UMLS CUI, values of drug attributes are ATC codes