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Transcriptome Analysis Read chapter Read first chapter

2012 | OriginalPaper | Chapter

Transcriptome Data Analysis for Cell Culture Processes

Authors : Marlene Castro-Melchor, Huong Le, Wei-Shou Hu

Published in: Genomics and Systems Biology of Mammalian Cell Culture

Publisher: Springer Berlin Heidelberg

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Abstract

In the past decade, DNA microarrays have fundamentally changed the way we study complex biological systems. By measuring the expression levels of thousands of transcripts, the paradigm of studying organisms has shifted from focusing on the local phenomena of a few genes to surveying the whole genome. DNA microarrays are used in a variety of ways, from simple comparisons between two samples to more intricate time-series studies. With the large number of genes being studied, the dimensionality of the problem is inevitably high. The analysis of microarray data thus requires specific approaches. In the case of time-series microarray studies, data analysis is further complicated by the correlation between successive time points in a series.
In this review, we survey the methodologies used in the analysis of static and time-series microarray data, covering data pre-processing, identification of differentially expressed genes, profile pattern recognition, pathway analysis, and network reconstruction. When available, examples of their use in mammalian cell cultures are presented.

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Metadata
Title
Transcriptome Data Analysis for Cell Culture Processes
Authors
Marlene Castro-Melchor
Huong Le
Wei-Shou Hu
Copyright Year
2012
Publisher
Springer Berlin Heidelberg
Book
Genomics and Systems Biology of Mammalian Cell Culture

Print ISBN: 978-3-642-28349-9

Electronic ISBN: 978-3-642-28350-5

Copyright Year: 2012

DOI
https://doi.org/10.1007/10_2011_116

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