Abstract
The Signaling and Dynamic Regulatory Events Miner (SDREM) is a powerful computational approach for identifying which signaling pathways and transcription factors control the temporal cellular response to a stimulus. SDREM builds end-to-end response models by combining condition-independent protein–protein interactions and transcription factor binding data with two types of condition-specific data: source proteins that detect the stimulus and changes in gene expression over time. Here we describe how to apply SDREM to study human diseases, using epidermal growth factor (EGF) response impacting neurogenesis and Alzheimer’s disease as an example.
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Acknowledgements
This work was supported by National Institutes of Health (1RO1 GM085022) and National Science Foundation (DBI-0965316) awards to Z.B.J. A.G. is supported by Microsoft Research.
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Gitter, A., Bar-Joseph, Z. (2016). The SDREM Method for Reconstructing Signaling and Regulatory Response Networks: Applications for Studying Disease Progression. In: Castrillo, J., Oliver, S. (eds) Systems Biology of Alzheimer's Disease. Methods in Molecular Biology, vol 1303. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2627-5_30
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DOI: https://doi.org/10.1007/978-1-4939-2627-5_30
Publisher Name: Humana Press, New York, NY
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Online ISBN: 978-1-4939-2627-5
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