Using knowledge-driven genomic interactions for multi-omics data analysis: Metadimensional models for predicting clinical outcomes in ovarian carcinoma

It is common that cancer patients have different molecular signatures even though they have similar clinical features, such as histology, due to the heterogeneity of tumors. To overcome this variability, we previously developed a new approach incorporating prior biological knowledge that identifies knowledge-driven genomic interactions associated with outcomes of interest.