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OMICS. 2006 Fall;10(3):398-410.

Functional interpretation of microarray experiments.

Author information

  • Department of Bioinformatics, and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain. jdopazo@cipf.es

Abstract

Over the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.

PMID:
17069516
[PubMed - indexed for MEDLINE]
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