Network-based cancer heterogeneity analysis incorporating multi-view of prior information.

ABSTRACT:

Motivation

Cancer genetic heterogeneity analysis has critical implications for tumour classification, response to therapy and choice of biomarkers to guide personalized cancer medicine. However, existing heterogeneity analysis based solely on molecular profiling data usually suffers from a lack of information and has limited effectiveness. Many biomedical and life sciences databases have accumulated a substantial volume of meaningful biological information. They can provide additional information beyond molecular profiling data, yet pose challenges arising from potential noise and uncertainty.

Results

In this study, we aim to develop a more effective heterogeneity analysis method with the help of prior information. A network-based penalization technique is proposed to innova

SUBMITTER: Li Y 

PROVIDER: S-EPMC9113254 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature