Unsupervised Meta-Analysis on Diverse Gene Expression Datasets Allows Insight into Gene Function and Regulation

Unsupervised Meta-Analysis on Diverse Gene Expression Datasets Allows Insight into Gene Function and Regulation

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Over the past years, microarray databases have increased rapidly in size. While they offer a wealth of data, it remains challenging to integrate data arising from different studies. Here we propose an unsupervised approach of a large-scale meta-analysis on Arabidopsis thaliana whole genome expressio...

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Bibliographic Details
Main Authors: Julia C. Engelmann, Roland Schwarz, Steffen Blenk, Torben Friedrich, Philipp N. Seibel, Thomas Dandekar, Tobias Müller
Format: Article
Language:English
Published: SAGE Publishing 2008-01-01
Series:Bioinformatics and Biology Insights
Subjects:
Arabidopsis thaliana
microarray
unsupervised meta-analysis
function prediction
database
gene expression
Online Access:http://la-press.com/article.php?article_id=822

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http://la-press.com/article.php?article_id=822

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