Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.
Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other [...]
Author(s): Kim, Dokyoon, Joung, Je-Gun, Sohn, Kyung-Ah, Shin, Hyunjung, Park, Yu Rang, Ritchie, Marylyn D, Kim, Ju Han
DOI: 10.1136/amiajnl-2013-002481