Clustering of temporal gene expression data with mixtures of mixed effects models
While time-dependent processes are important to biological functions, methods to leverage temporal information from large data have remained computationally challenging. In temporal gene-expression data, clustering can be used to identify genes with shared function in complex processes. Algorithms...
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Language: | en_US |
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2019
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Online Access: | https://hdl.handle.net/2144/34905 |