Computational biomarker discovery

Fan Zhang, Xiaogang Wu, Jake Y. Chen

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

The advent of omics technologies as genomics and proteomics has brought the hope of discovering novel biomarkers that can be used to diagnose, predict, and monitor progress of disease. The importance of computational biomarker discovery for diagnostic classification and prognostic assessment in the context of microarray and proteomic data has been increasingly recognized. We present an overview of computational methods and their applications to biomarker discovery with particular focus on genomics and proteomics data. One case study is exemplarily presented, and relevant computational biomarker discovery terminology and techniques are explained.

Original languageEnglish
Title of host publicationApproaches in Integrative Bioinformatics
Subtitle of host publicationTowards the Virtual Cell
PublisherSpringer Berlin Heidelberg
Pages355-386
Number of pages32
ISBN (Electronic)9783642412813
ISBN (Print)9783642412806
DOIs
StatePublished - 1 Jan 2014

Keywords

  • Biomarker discovery
  • Breast cancer
  • Data mining

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  • Cite this

    Zhang, F., Wu, X., & Chen, J. Y. (2014). Computational biomarker discovery. In Approaches in Integrative Bioinformatics: Towards the Virtual Cell (pp. 355-386). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-41281-3_13