Bioinformatics tools for cancer metabolomics

Journal Article (Journal Article)

It is well known that significant metabolic change take place as cells are transformed from normal to malignant. This review focuses on the use of different bioinformatics tools in cancer metabolomics studies. The article begins by describing different metabolomics technologies and data generation techniques. Overview of the data pre-processing techniques is provided and multivariate data analysis techniques are discussed and illustrated with case studies, including principal component analysis, clustering techniques, self-organizing maps, partial least squares, and discriminant function analysis. Also included is a discussion of available software packages. © 2011 The Author(s).

Full Text

Duke Authors

Cited Authors

  • Blekherman, G; Laubenbacher, R; Cortes, DF; Mendes, P; Torti, FM; Akman, S; Torti, SV; Shulaev, V

Published Date

  • September 1, 2011

Published In

Volume / Issue

  • 7 / 3

Start / End Page

  • 329 - 343

Electronic International Standard Serial Number (EISSN)

  • 1573-3890

International Standard Serial Number (ISSN)

  • 1573-3882

Digital Object Identifier (DOI)

  • 10.1007/s11306-010-0270-3

Citation Source

  • Scopus