Cancer is one of the most complex diseases and there
are currently more than 100 known types of cancers in humans.
The most widely accepted theory is that cancer is mainly caused by genetic mutations.
A key issue and major challenge is to distinguish the driver mutations from the massive passengers.
we present a new method termed DriverMP
(Multiomics-based Pair driver genes) for effectively prioritizing altered genes
on a cancer type level by considering mutation pair genes.
It is designed by first applying somatic mutation data, protein-protein interaction network,
and differential gene expression data to prioritizing mutation pairs, based on which individual
mutated
genes are then prioritized. The new approach effectively improves the identification of driver
mutations
mainly by the following contributions.