In April 2016 Manchester eScholar was replaced by the University of Manchester’s new Research Information Management System, Pure. In the autumn the University’s research outputs will be available to search and browse via a new Research Portal. Until then the University’s full publication record can be accessed via a temporary portal and the old eScholar content is available to search and browse via this archive.

Bioinformatics tools for cancer metabolomics

Grigoriy Blekherman, Reinhard Laubenbacher, Diego F. Cortes, Pedro Mendes, Frank M. Torti, Steven Akman, Suzy V. Torti, Vladimir Shulaev

Metabolomics. 2011;7:329-343.

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Abstract

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.

Institutional metadata

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Record metadata

Manchester eScholar ID:
uk-ac-man-scw:154870
Created by:
Pedrosa Mendes, Pedro
Created:
31st January, 2012, 12:56:47
Last modified by:
Pedrosa Mendes, Pedro
Last modified:
31st January, 2012, 12:56:47

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