ArticleBMC genomics2009
Improving gene expression similarity measurement using pathway-based analytic dimension.
Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Pathprinting: An integrative approach to understand the functional basis of disease.Genome medicine · 2013Article
- Differential effects of procaspase-3 activating compounds in the induction of cancer cell death.Molecular pharmaceutics · 2012Article
- Comparison and evaluation of pathway-level aggregation methods of gene expression data.BMC genomics · 2012Article
- Extending Asia Pacific bioinformatics into new realms in the "-omics" era.BMC genomics · 2009Article
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5 authors.
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Abstract
backgroundGene expression similarity measuring methods were developed and applied to search rapidly growing public microarray databases. However, current expression similarity measuring methods need to be improved to accurately measure similarity between gene expression profiles from different platforms or different experiments.
resultsWe devised new gene expression similarity measuring method based on pathway information. In short, newly devised method measure similarity between gene expression profiles after converting them into pathway based expression profiles. To evaluate pathway based gene expression similarity measuring method, we conducted cell type classification test. Pathway based similarity measuring method shows higher classification accuracy. Especially, pathway based methods outperform at most 50% and 10% over conventional gene expression similarity method when search databases are limited to cross-platform profiles and cross-experiment profiles.
conclusionThe pathway based gene expression similarity measuring method outperforms commonly used similarity measuring methods. Considering the fact that public microarray database is consist of gene expression profiles of various experiments with various type of platform, pathway based gene expression similarity measuring method could be successfully applied for searching large public microarray databases.
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