Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
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Abstract
Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many…
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56,260
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- FWCI
- 106.76
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- 100%
- References
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Authors
11Topics & keywords
Topics
Keywords
- Computational biology
- Gene
- Biology
- Function (biology)
- Gene expression
- Set (abstract data type)
- Genome
- Gene nomenclature
UN Sustainable Development Goals
- Good health and well-being
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