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Analysis and understanding of high-dimensionality data by means of multivariate data analysis

Norden, B ; Broberg, P ; Lindberg, C and Plymoth, Amelie LU (2005) In Chemistry and Biodiversity 2(11). p.1487-1494
Abstract
Multivariate analysis such as principal-components analysis (PCA) and partial-least-squares-discriminant analysis (PLS-DA) have been applied to peptidomics data from clinical urine samples subjected to LC/MS analysis. We show that it is possible to use these methods to get information from a complex set of clinical data. The aim of the work is to use this information as a first step in the further search for clinical biomarker data. It is possible to identify peptide-biomarker fingerprints related to disease diagnosis and progression. Further, we review clinical proteomics and pharmacogenomics data analyzed with the same multivariate approach.
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Chemistry and Biodiversity
volume
2
issue
11
pages
1487 - 1494
publisher
Verlag Helvetica Chimica Acta
external identifiers
  • wos:000233692500007
  • scopus:28844504146
  • pmid:17191948
ISSN
1612-1872
DOI
10.1002/cbdv.200590120
language
English
LU publication?
yes
id
d710a056-c12d-4576-aaf3-45c6ec4f16ca (old id 211870)
date added to LUP
2016-04-01 12:33:08
date last changed
2022-01-27 06:38:34
@article{d710a056-c12d-4576-aaf3-45c6ec4f16ca,
  abstract     = {{Multivariate analysis such as principal-components analysis (PCA) and partial-least-squares-discriminant analysis (PLS-DA) have been applied to peptidomics data from clinical urine samples subjected to LC/MS analysis. We show that it is possible to use these methods to get information from a complex set of clinical data. The aim of the work is to use this information as a first step in the further search for clinical biomarker data. It is possible to identify peptide-biomarker fingerprints related to disease diagnosis and progression. Further, we review clinical proteomics and pharmacogenomics data analyzed with the same multivariate approach.}},
  author       = {{Norden, B and Broberg, P and Lindberg, C and Plymoth, Amelie}},
  issn         = {{1612-1872}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{1487--1494}},
  publisher    = {{Verlag Helvetica Chimica Acta}},
  series       = {{Chemistry and Biodiversity}},
  title        = {{Analysis and understanding of high-dimensionality data by means of multivariate data analysis}},
  url          = {{http://dx.doi.org/10.1002/cbdv.200590120}},
  doi          = {{10.1002/cbdv.200590120}},
  volume       = {{2}},
  year         = {{2005}},
}