Functional Interpretation of Microarray Experiments
- 1 September 2006
- journal article
- research article
- Published by Mary Ann Liebert Inc in OMICS: A Journal of Integrative Biology
- Vol. 10 (3), 398-410
- https://doi.org/10.1089/omi.2006.10.398
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.Keywords
This publication has 64 references indexed in Scilit:
- Next station in microarray data analysis: GEPASNucleic Acids Research, 2006
- Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profilesProceedings of the National Academy of Sciences, 2005
- Towards a proteome-scale map of the human protein–protein interaction networkNature, 2005
- Ontological analysis of gene expression data: current tools, limitations, and open problemsBioinformatics, 2005
- The evolution of molecular biology into systems biologyNature Biotechnology, 2004
- GO::TermFinder—open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genesBioinformatics, 2004
- Statistical significance for genomewide studiesProceedings of the National Academy of Sciences, 2003
- PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetesNature Genetics, 2003
- Gene expression profiling predicts clinical outcome of breast cancerNature, 2002
- The control of the false discovery rate in multiple testing under dependencyThe Annals of Statistics, 2001