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PubMed · 16355722

An integrated strategy for the optimization of microarray data interpretation.

Xinmin Li·Richard J Quigg
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Abstract

The completion of a microarray experiment represents just a starting point toward understanding the biology of interest. A follow-up strategy is needed to fully elucidate the functional significance of microarray-derived measurements of differential expression. Given the fact that no single approach can fully unravel the fundamental biology that is typically quite complex, the follow-up strategy must be integrated at multiple levels encompassing bioinformatics, genomics, and proteomics. In this review, we discuss an integrative approach, which can be used to prioritize microarray-derived candidate genes, define their functions, and place them in the context of the biological system being studied.

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AnimalsChromosome MappingComputational BiologyDatabases, Nucleic AcidDatabases, ProteinGene Expression ProfilingGenomicsHumansMiceOligonucleotide Array Sequence AnalysisProteomicsQuantitative Trait LociRatsJournal ArticleReview

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Xinmin Li, Richard J Quigg. 2005. An integrated strategy for the optimization of microarray data interpretation.. https://doi.org/10.3727/000000005783991990

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