We characterized miRNA-gene interactions in over 2000 REACTOME pathways in dendritic cells used for immunotherapy. All the identified interactions are visualized in complex heat maps accompanied with a table for detailed information for further research.

The database contains cooperative miRNA pairs that are predicted for efficiently modulating the expression of protein-coding genes of cancer driver genes underlying metastatic melanoma.

The pipeline builds a deep learning model based on disease networks. The learned representations are used for patient stratification, and  in turn, the data mined in the network provides biomedical explanation to the deep learning model.

The pipeline presents a network-based method for identifying cancer genes that can be used as prognostic and prognostic biomarkers and a advanced drug repurposing method targeting those cancer.

The multi-level mathematical model accounts for the anti-cancer effects of an immune vaccine at the molecular level and can be used for optimizing the vaccine design.