Simultaneous Reconstruction of Multiple Signaling Pathways via the Prize-Collecting Steiner Forest Problem

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Date

2013-02-01

Author

Tunçbağ, Nurcan
PAGNANI, Andrea
Huang, Shao-Shan Carol
CHAYES, Jennifer
BORGS, Christian
Zecchina, Riccardo
FRAENKEL, Ernest

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Signaling and regulatory networks are essential for cells to control processes such as growth, differentiation, and response to stimuli. Although many "omic'' data sources are available to probe signaling pathways, these data are typically sparse and noisy. Thus, it has been difficult to use these data to discover the cause of the diseases and to propose new therapeutic strategies. We overcome these problems and use "omic'' data to reconstruct simultaneously multiple pathways that are altered in a particular condition by solving the prize-collecting Steiner forest problem. To evaluate this approach, we use the well-characterized yeast pheromone response. We then apply the method to human glioblastoma data, searching for a forest of trees, each of which is rooted in a different cell-surface receptor. This approach discovers both overlapping and independent signaling pathways that are enriched in functionally and clinically relevant proteins, which could provide the basis for new therapeutic strategies. Although the algorithm was not provided with any information about the phosphorylation status of receptors, it identifies a small set of clinically relevant receptors among hundreds present in the interactome.

Subject Keywords

Multiple network reconstruction, Prize-collecting Steiner forest, Signaling pathways

URI

https://hdl.handle.net/11511/31736

Journal

JOURNAL OF COMPUTATIONAL BIOLOGY

DOI

https://doi.org/10.1089/cmb.2012.0092

Collections

Graduate School of Informatics, Article

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Simultaneous reconstruction of multiple signaling pathways via the prize collecting Steiner forest problem Tunçbağ, Nurcan; PAGNANI, ANDREA; HUANG, SHAO SHAN CAROL; CHAYES, JENNIFER; BORGS, CHRISTIAN; ZECCHINA, RICCARDO; FRAENKEL, ERNEST (2012-04-13) Signaling networks are essential for cells to control processes such as growth and response to stimuli. Although many “omic” data sources are available to probe signaling pathways, these data are typically sparse and noisy. Thus, it has been difficult to use these data to discover the cause of the diseases. We overcome these problems and use “omic” data to simultaneously reconstruct multiple pathways that are altered in a particular condition by solving the prize-collecting Steiner forest problem. To evalua...
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Citation Formats

N. Tunçbağ et al., “Simultaneous Reconstruction of Multiple Signaling Pathways via the Prize-Collecting Steiner Forest Problem,” JOURNAL OF COMPUTATIONAL BIOLOGY, pp. 124–136, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31736.