A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series-Reference-Cited by-同舟云学术

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series

Published:2010-03 Issue:3 Volume:17 Page:355-367
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Stegle Oliver¹,Denby Katherine J.²,Cooke Emma J.³,Wild David L.⁴,Ghahramani Zoubin⁵,Borgwardt Karsten M.¹

Affiliation:

1. Interdepartmental Bioinformatics Group, Max Planck Institute for Developmental Biology, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.

2. Warwick HRI & Warwick Systems Biology, Wellesbourne, Warks, United Kingdom.

3. MOAC Doctoral Training Centre, University of Warwick, Coventry, United Kingdom.

4. Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.

5. Department of Engineering, University of Cambridge, Cambridge, United Kingdom.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/cmb.2009.0175

Reference20 articles.

1. Benchmarking the CATMA Microarray. A Novel Tool forArabidopsis Transcriptome Analysis

2. BATS: a Bayesian user-friendly software for Analyzing Time Series microarray experiments

3. Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes

4. maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments

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