Over the past years growing knowledge about biological processes and pathways revealed complex interaction networks involving many genes. In order to understand these networks, analysis of differential expression has continuously moved from single genes towards the study of gene sets. Various approaches for the assessment of gene sets have been developed in the context of gene set analysis (GSA). These approaches are bridging the gap between raw measurements and semantically meaningful terms.
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