Abstract
This paper presents our computational and measurement strategy for investigating gene networks from gene expression data using state space model and dynamic Bayesian network model with nonparametric regression. These methods are applied to gene expression data based on gene knockdowns and drug responses for generating large global maps of gene regulation which will light up the geography where drug target pathways lie down.
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Miyano, S., Yamaguchi, R., Tamada, Y., Nagasaki, M., Imoto, S. (2009). Gene Networks Viewed through Two Models. In: Rajasekaran, S. (eds) Bioinformatics and Computational Biology. BICoB 2009. Lecture Notes in Computer Science(), vol 5462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00727-9_8
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DOI: https://doi.org/10.1007/978-3-642-00727-9_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00726-2
Online ISBN: 978-3-642-00727-9
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