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

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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Detalles Bibliográficos
Autores principales: Engelmann, Julia C., Schwarz, Roland, Blenk, Steffen, Friedrich, Torben, Seibel, Philipp N., Dandekar, Thomas, Müller, Tobias
Formato: Texto
Lenguaje:English
Publicado: Libertas Academica 2008
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2735942/
https://www.ncbi.nlm.nih.gov/pubmed/19812781

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2735942/
https://www.ncbi.nlm.nih.gov/pubmed/19812781

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