We next downloaded all drug data available online from DrugBank [19]. We extracted drug targets and converted all gene names to the Entrez gene identifier. Only drugs that were included in CMap and have a gene target that was measured were included in downstream analysis.

We extracted all human pathways from Reactome [20] and connected all pathways into one large network. Only genes that were measured in CMap were included. Undirected edges from Reactome are represented as two directed edges in opposite directions.

As shown in Fig 1, step 1, each circular node represents a gene, and each directed arrow represents an interaction from Reactome. We next add drug nodes, depicted as triangles, to the overall network or genes (Fig 1, step 1). A drug may have multiple targets, which would be represented as having multiple outgoing edges. Similarly, a gene may be the target of multiple drugs, depicted by multiple incoming edges.

(1) Drugs, drug targets, genes, and gene interactions are curated from DrugBank and Reactome to form a gene-drug network. (2) The expression of each gene is modeled as a linear regression of incoming nodes, where the coefficient parameters are learned from the Connectivity Map. (3) IBD data is curated from the Gene Expression Omnibus (GEO), and for each sample (4) a drugged IBD sample is created using the network. (5) The healthy samples are averaged to create a healthy patient representation, and (6) each drugged IBD sample is compared to the healthy sample using Euclidean distance to create a personalized ranked drug list.

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