Unification of Gene Expression Data for Comparable Analyses Under Stress Conditions
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Gene expression is a fundamental biological process in which genotypes rise to phenotypes. As a quantitative measurement, expression of a gene is commonly examined by mRNA abundance that varies in response to different conditions and environmental stimuli. High throughput quantitative measurements of gene expression data have difficulties of reproducibility and comparability due to a lack of standard mRNA quantification references. Efforts have been made to safeguard data fidelity, yet generating quality expression data of inherent value remains a challenge. This not only affects unbiased data assessment and clinical applications but also damages establishing invaluable database resources for the larger scientific community. Unification of multi-source gene expression data is necessary for comparable and comprehensive analyses to gain insight into complex gene interactions and regulatory networks of life events using more integrated approaches of bioinformatics, computational biology and systems biology. Development and application of commonly accepted quantification references to generate comparable expression data are urgently needed. This chapter provides basics and application aspects for comparative gene expression analyses using microbial examples under stress conditions.
KeywordsGene Expression Data Master Equation Microarray Assay Target Array Assay Platform
The author is grateful to Michael A. Cotta and Marsha Ebener for proofreading of the manuscript. This work was supported in part by NIFA National Research Initiative Award 2006-35504-17359. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. USDA is an equal opportunity provider and employer.
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