STEM: a tool for the analysis of short time series gene expression data |
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Authors: | Jason Ernst and Ziv Bar-Joseph |
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Institution: | (1) Center for Automated and Learning and Discovery, School of Computer Science, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA |
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Abstract: | Background Time series microarray experiments are widely used to study dynamical biological processes. Due to the cost of microarray
experiments, and also in some cases the limited availability of biological material, about 80% of microarray time series experiments
are short (3–8 time points). Previously short time series gene expression data has been mainly analyzed using more general
gene expression analysis tools not designed for the unique challenges and opportunities inherent in short time series gene
expression data. |
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Keywords: | |
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