Empirical Inference Conference Paper 2009

Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series

A wealth of time series of microarray measurements have become available over recent years. Several two-sample tests for detecting differential gene expression in these time series have been defined, but they can only answer the question whether a gene is differentially expressed across the whole time series, not in which intervals it is differentially expressed. In this article, we propose a Gaussian process based approach for studying these dynamics of differential gene expression. In experiments on Arabidopsis thaliana gene expression levels, our novel technique helps us to uncover that the family of WRKY transcription factors appears to be involved in the early response to infection by a fungal pathogen.

Author(s): Stegle, O. and Denby, KJ. and Wild, DL. and McHattie, S. and Mead, A. and Ghahramani, Z. and Borgwardt, KM.
Journal: Proceedings of the German Conference on Bioinformatics 2009 (GCB 2009)
Pages: 133-142
Year: 2009
Month: September
Day: 0
Editors: Grosse, I. , S. Neumann, S. Posch, F. Schreiber, P. F. Stadler
Publisher: Gesellschaft f{\"u}r Informatik
Bibtex Type: Conference Paper (inproceedings)
Address: Bonn, Germany
Event Name: German Conference on Bioinformatics 2009 (GCB ’09)
Event Place: Halle, Germany
Digital: 0
Electronic Archiving: grant_archive
ISBN: 978-3-88579-251-2
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

@inproceedings{6295,
  title = {Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series},
  journal = {Proceedings of the German Conference on Bioinformatics 2009 (GCB 2009)},
  abstract = {A wealth of time series of microarray measurements have become available over recent years. Several two-sample tests for detecting differential gene expression
  in these time series have been defined, but they can only answer the question whether a gene is differentially expressed across the whole time series, not in which intervals it is differentially expressed. In this article, we propose a Gaussian process based approach for studying these dynamics of differential gene expression. In experiments on Arabidopsis thaliana gene expression levels, our novel technique helps us to uncover that the family of WRKY transcription factors appears to be involved in the early response to infection by a fungal pathogen.},
  pages = {133-142},
  editors = {Grosse, I. , S. Neumann, S. Posch, F. Schreiber, P. F. Stadler},
  publisher = {Gesellschaft f{\"u}r Informatik},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Bonn, Germany},
  month = sep,
  year = {2009},
  slug = {6295},
  author = {Stegle, O. and Denby, KJ. and Wild, DL. and McHattie, S. and Mead, A. and Ghahramani, Z. and Borgwardt, KM.},
  month_numeric = {9}
}