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- Title
Clustering short time series gene expression data.
- Authors
Ernst, Jason; Nau, Gerard J; Bar-Joseph, Ziv
- Abstract
Time series expression experiments are used to study a wide range of biological systems. More than 80% of all time series expression datasets are short (8 time points or fewer). These datasets present unique challenges. On account of the large number of genes profiled (often tens of thousands) and the small number of time points many patterns are expected to arise at random. Most clustering algorithms are unable to distinguish between real and random patterns.
- Publication
Bioinformatics (Oxford, England), 2005, Vol 21 Suppl 1, pi159
- ISSN
1367-4803
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/bti1022