Gene set enrichment; a problem of pathways
Davies, M.N. and Meaburn, Emma L. and Schalkwyk, L.C. (2010) Gene set enrichment; a problem of pathways. Briefings in Functional Genomics 9 (5-6), pp. 385-90. ISSN 2041-2649.
Gene Set Enrichment (GSE) is a computational technique which determines whether a priori defined set of genes show statistically significant differential expression between two phenotypes. Currently, the gene sets used for GSE are derived from annotation or pathway databases, which often contain computationally based and unrepresentative data. Here, we propose a novel approach for the generation of comprehensive and biologically derived gene sets, deriving sets through the application of machine learning techniques to gene expression data. These gene sets can be produced for specific tissues, developmental stages or environments. They provide a powerful and functionally meaningful way in which to mine genomewide association and next generation sequencing data in order to identify disease-associated variants and pathways.
|Keyword(s) / Subject(s):||gene set enrichment, annotation database, gene expression data, machine learning, next generation sequencing|
|School:||Birkbeck Schools and Departments > School of Science > Psychological Sciences|
|Research Centre:||Educational Neuroscience, Centre for, Brain and Cognitive Development, Centre for (CBCD)|
|Depositing User:||Emma Meaburn|
|Date Deposited:||15 May 2013 09:35|
|Last Modified:||09 Dec 2016 11:16|
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