Pathway and network approaches for identification of cancer signature markers from omics data

Jinlian Wang, Yiming Zuo, Yan gao Man, Itzhak Avital, Alexander Stojadinovic, Meng Liu, Xiaowei Yang, Rency S. Varghese, Mahlet G. Tadesse, Habtom W. Ressom

Research output: Contribution to journalArticle

22 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)54-65
Number of pages12
JournalJournal of Cancer
Volume6
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes

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Keywords

  • Biological pathways
  • Cancer biomarker
  • High-throughput omics data
  • System biology

ASJC Scopus subject areas

  • Oncology

Cite this

Wang, J., Zuo, Y., Man, Y. G., Avital, I., Stojadinovic, A., Liu, M., Yang, X., Varghese, R. S., Tadesse, M. G., & Ressom, H. W. (2015). Pathway and network approaches for identification of cancer signature markers from omics data. Journal of Cancer, 6(1), 54-65. https://doi.org/10.7150/jca.10631