Ontology highlight
ABSTRACT:
SUBMITTER: Guo J
PROVIDER: S-EPMC3937336 | biostudies-literature | 2014
REPOSITORIES: biostudies-literature
Guo Jun J Guo Hanliang H Wang Zhanyi Z
PloS one 20140227 2
The temporal order of cancer gene mutations in tumors is essential for understanding and treating the disease. Existing methods are unable to infer the order of mutations that are identified at the same time in individual tumor samples, leaving the heterogeneity of the order unknown. Here, we show that through a complex network-based approach, which is based on the newly defined statistic -carcinogenesis information conductivity (CIC), the temporal order in individual samples can be effectively ...[more]