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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/10335

Title: Mining multiple biological data for reconstructing signal transduction networks
Authors: Nguyen, Thanh-Phuong
Ho, Tu-Bao
Keywords: signal transduction network reconstruction
multiple biological data
Issue Date: 2012
Publisher: Springer
Volume: 25
Start page: 163
End page: 185
DOI: 10.1007/978-3-642-23151-3_8
Abstract: Signaling transduction networks (STNs) are the key means by which a cell converts an external signal (e.g. stimulus) into an appropriate cellular response (e.g. cellular rhythms of animals and plants). The essence of STN is underlain in some signaling features scattered in various data sources and biological components overlapping among STN. The integration of those signaling features presents a challenge. Most of previous works based on PPIs for STN did not take the signaling properties of signaling molecules and components overlapping among STN into account. This paper describes an effective computational method that can exploit three biological facts of STN applied to human: protein-protein interaction networks, signaling features and sharing components. To this end, we introduce a soft-clustering method for doing the task by exploiting integrated multiple data, especially signaling features, i.e., protein-protein interactions, signaling domains, domain-domain interactions, and protein functions. The gained results demonstrated that the method was promising to discover new STN and solve other related problems in computational and systems biology from large-scale protein interaction networks. Other interesting results of the early work on yeast STN are additionally presented to show the advantages of using signaling domain-domain interactions.
Rights: This is the author-created version of Springer, Thanh-Phuong Nguyen and Tu-Bao Ho, Data Mining: Foundations and Intelligent Paradigms, 25, 2012, pp.163-185. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-642-23151-3_8
URI: http://hdl.handle.net/10119/10335
Material Type: author
Appears in Collections:a10-2. 図書 (Book, Book Chapter)

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