title: Pathway and network approaches for identification of cancer signature markers from omics data.
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.
authors.affiliation: 1. Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA; ; 7. Genetics and Genomics Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
authors.forename: Jinlian
authors.initials: J
authors.lastname: Wang
authors.affiliation: 1. Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA; ; 6. Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA, USA;
authors.forename: Yiming
authors.initials: Y
authors.lastname: Zuo
authors.affiliation: 2. Bon Secours Cancer Institute, Richmond VA, USA;
authors.forename: Yan-Gao
authors.initials: YG
authors.lastname: Man
authors.affiliation: 2. Bon Secours Cancer Institute, Richmond VA, USA;
authors.forename: Itzhak
authors.initials: I
authors.lastname: Avital
authors.affiliation: 2. Bon Secours Cancer Institute, Richmond VA, USA; ; 3. Division of Surgical Oncology, Walter Reed National Military Medical Center, Bethesda, MD, USA;
authors.forename: Alexander
authors.initials: A
authors.lastname: Stojadinovic
authors.affiliation: 4. Department of Public Health School of Hunter College, City University of New York, NYC, USA;
authors.forename: Meng
authors.initials: M
authors.lastname: Liu
authors.affiliation: 4. Department of Public Health School of Hunter College, City University of New York, NYC, USA;
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Yang
authors.affiliation: 1. Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA;
authors.forename: Rency S
authors.initials: RS
authors.lastname: Varghese
authors.affiliation: 5. Department of Mathematics and Statistics, Georgetown University, Washington DC, USA;
authors.forename: Mahlet G
authors.initials: MG
authors.lastname: Tadesse
authors.affiliation: 1. Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA;
authors.forename: Habtom W
authors.initials: HW
authors.lastname: Ressom
keywords: Biological pathways; cancer biomarker.; high-throughput omics data; system biology