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Bayesian coclustering of Anopheles gene expression time series: study of immune defense response to multiple experimental challenges.

Abstract:

We present a method for Bayesian model-based hierarchical coclustering of gene expression data and use it to study the temporal transcription responses of an Anopheles gambiae cell line upon challenge with multiple microbial elicitors. The method fits statistical regression models to the gene expression time series for each experiment and performs coclustering on the genes by optimizing a joint probability model, characterizing gene coregulation between multiple experiments. We compute the mo...

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Publication status:
Published

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Publisher copy:
10.1073/pnas.0408393102

Authors


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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics, Clinical Medicine
Role:
Author
Journal:
Proceedings of the National Academy of Sciences of the United States of America
Volume:
102
Issue:
47
Pages:
16939-16944
Publication date:
2005-11-05
DOI:
EISSN:
1091-6490
ISSN:
0027-8424
URN:
uuid:c308b0cb-8637-475e-8b2e-e4ff4b885b3c
Source identifiers:
97550
Local pid:
pubs:97550

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