Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data

Authors

Jinlian Wang, Georgetown University
Yiming Zuo, Georgetown University
Yan-gao Man, Bon Secours Cancer Institute
Itzhak Avital, Bon Secours Cancer Institute
Alexander Stojadinovic, Bon Secours Cancer Institute
Meng Liu, CUNY Hunter College
Xiaowei Yang, CUNY Hunter College
Rency S. Varghese, Georgetown University
Mahlet G. Tadesse, Georgetown University
Habtom W. Ressom, Georgetown University

Document Type

Article

Publication Date

January 2015

Abstract

The advancement of high throughput omic technologies during the past few years has made it possible to perform many complex assays in a much shorter time than the traditional approaches. The rapid accumulation and wide availability of omic data generated by these technologies offer great opportunities to unravel disease mechanisms, but also presents significant challenges to extract knowledge from such massive data and to evaluate the findings. To address these challenges, a number of pathway and network based approaches have been introduced. This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.

Comments

This work was originally published in Journal of Cancer, available at doi:10.7150/jca.10631.