Analysis and understanding of high-dimensionality data by means of multivariate data analysis
(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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/211870
- author
- Norden, B ; Broberg, P ; Lindberg, C and Plymoth, Amelie LU
- organization
- publishing date
- 2005
- 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}}, }