Recursive regularization for inferring gene networks from time-course gene expression profiles |
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Authors: | Teppei Shimamura Seiya Imoto Rui Yamaguchi André Fujita Masao Nagasaki Satoru Miyano |
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Institution: | (1) Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku Tokyo, 108-8639, Japan |
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Abstract: | Background Inferring gene networks from time-course microarray experiments with vector autoregressive (VAR) model is the process of identifying
functional associations between genes through multivariate time series. This problem can be cast as a variable selection problem
in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005). However,
VAR modeling with the elastic net succeeds in increasing the number of true positives while it also results in increasing
the number of false positives. |
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Keywords: | |
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