DocumentCode :
2528246
Title :
Joint genomic and metabolomic analysis of toxic dose-response experiments
Author :
Jahns, Gary L. ; DelRaso, Nicholas ; Westrick, Mark P. ; Chan, Victor ; Reo, Nicholas V. ; Zacharewski, Timothy R.
Author_Institution :
BAE Syst. Adv. Inf. Technol., San Diego, CA, USA
fYear :
2005
fDate :
8-11 Aug. 2005
Firstpage :
195
Lastpage :
196
Abstract :
A methodology has been implemented for analyzing microarray and NMR spectral data obtained from the same set of toxic-exposure dose-response experiments. The NMR spectra additionally track the time course of exposure. Analyses consist of screening the data to eliminate variates with insignificant signal, normalization appropriate to the experimental design, principal components analysis, and nonlinear classification using a support vector machine. It is found that exposure at subtoxic levels can be detected.
Keywords :
biological NMR; biology computing; genetics; learning (artificial intelligence); molecular biophysics; principal component analysis; support vector machines; toxicology; NMR spectral data; genomic analysis; metabolomic analysis; microarray analysis; nonlinear classification; principal components analysis; support vector machine; toxic dose-response; Bioinformatics; Genomics; Metabolomics; Nuclear magnetic resonance; Performance analysis; Principal component analysis; Probes; Signal analysis; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE
Print_ISBN :
0-7695-2442-7
Type :
conf
DOI :
10.1109/CSBW.2005.81
Filename :
1540596
Link To Document :
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