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Content Provider | IEEE Xplore Digital Library |
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Author | Song, J.Z. Duan, K.M. Surette, M. |
Copyright Year | 2005 |
Description | Author affiliation: Department of Microbiology and Infectious Diseases, University of Calgary (Song, J.Z.) |
Abstract | A variety of high throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy for can be applied in the analysis of data sets of thousands of genes during cellular differentiation and response. |
Starting Page | 148 |
Ending Page | 148 |
File Size | 318396 |
Page Count | 1 |
File Format | |
ISBN | 0769523722 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.2005.540 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-09-21 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Wavelet transforms Biochemical analysis Delay effects Hidden Markov models Production Wavelet analysis Throughput Gene expression Data mining Pattern analysis |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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