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Fig. 3 | BMC Bioinformatics

Fig. 3

From: RWRMTN: a tool for predicting disease-associated microRNAs based on a microRNA-target gene network

Fig. 3

A four-step workflow of RWRMTN for predicting breast cancer-associated miRNAs. Step1: Load datasets: a miRNA-target interaction dataset and a known disease-miRNA association dataset must be selected. Step 2: Rank candidate miRNAs: a disease of interest (e.g., breast cancer) is chosen, then a set of candidate miRNAs is specified and ranked. Step 3: Search Evidences: Top-ranked candidate miRNAs are selected and provided with evidence from literature about their associations with the disease of interest. Step 4: Rank-based visualization: the selected candidate miRNAs are visualized based on their rankings and their relationships with the disease of interest, known breast cancer-associated miRNAs and supporting PubMed IDs. These steps can be performed by either the Cytoscape menu or CyREST Command APIs called from other environments (e.g., R)

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