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Pathways to the analysis of microarray data
University of Cambridge Department of Clinical Biochemistry, Box 232, Addenbrooke’s Hospital, Hills Road, Cambridge, UK.
Technical Research Centre of Finland, VTT Biotechnology, Espoo, Finland.ORCID iD: 0000-0002-2856-9165
University of Cambridge Department of Clinical Biochemistry, Box 232, Addenbrooke’s Hospital, Hills Road, Cambridge, UK.
2005 (English)In: Trends in Biotechnology, ISSN 0167-7799, E-ISSN 1879-3096, Vol. 23, no 8, p. 429-435Article, review/survey (Refereed) Published
Abstract [en]

The development of microarray technology allows the simultaneous measurement of the expression of many thousands of genes. The information gained offers an unprecedented opportunity to fully characterize biological processes. However, this challenge will only be successful if new tools for the efficient integration and interpretation of large datasets are available. One of these tools, pathway analysis, involves looking for consistent but subtle changes in gene expression by incorporating either pathway or functional annotations. We review several methods of pathway analysis and compare the performance of three, the binomial distribution, z scores, and gene set enrichment analysis, on two microarray datasets. Pathway analysis is a promising tool to identify the mechanisms that underlie diseases, adaptive physiological compensatory responses and new avenues for investigation.

Place, publisher, year, edition, pages
Elsevier, 2005. Vol. 23, no 8, p. 429-435
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-70896DOI: 10.1016/j.tibtech.2005.05.011ISI: 000231342700010PubMedID: 15950303Scopus ID: 2-s2.0-22744458472OAI: oai:DiVA.org:oru-70896DiVA, id: diva2:1345893
Available from: 2019-08-26 Created: 2019-08-26 Last updated: 2019-09-05Bibliographically approved

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Oresic, Matej

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