Skip Navigation



ToxSci Advance Access published online on January 4, 2008
Toxicological Sciences, doi:10.1093/toxsci/kfn001
This Article
Right arrow Advance Access manuscript (PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
102/2/444    most recent
kfn001v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Spicker, J. S.
Right arrow Articles by Toft, H.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Spicker, J. S.
Right arrow Articles by Toft, H.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2008. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Integration of Clinical Chemistry, Expression, and Metabolite Data Leads to Better Toxicological Class Separation

Jeppe S. Spicker*,{dagger}, Søren Brunak*, Klaus S. Frederiksen§ and Henrik Toft{dagger}

* Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Lyngby, Denmark {dagger} Protein Structure and Biophysics, Protein Engineering, Novo Nordisk Park, DK-2760 Måløv, Denmark § Molecular Genetics, Biotechnology, Novo Nordisk Park, DK-2760 Måløv, Denmark

To whom correspondence should be addressed: Jeppe S. Spicker Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Lyngby, Denmark. Phone: +45 45252477. Fax: +45 45931585. Email: skytte{at}cbs.dtu.dk

Received August 29, 2007; revision received December 20, 2007; accepted December 21, 2007


  Abstract

A large number of databases are currently being implemented within toxicology aiming to integrate diverse biological data, such as clinical chemistry, expression, and other types of data. However, for these endeavours to be successful, tools for integration, visualization and interpretation are needed. This paper presents a method for data integration using a hierarchical model based on either principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) of clinical chemistry, expression, and nuclear magnetic resonance (NMR) data using a toxicological study as case. The study includes the three toxicants alpha-naphthyl-isocyante (ANIT), dimethylnitrosamine (DMN), and N-methylformamide (NMF) administered to rats. Improved predictive ability of the different classes is seen suggesting that this approach is a suitable method for data integration and visualization of biological data. Furthermore, the method allows for correlation of biological parameters between the different data types, which could lead to an improvement in biological interpretation.

Key Words: Data integration; toxicology; clinical chemistry; microarray; metabonomics.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.