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Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It syst...

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Autores principales: Kӧksal, Ali Sinan, Beck, Kirsten, Cronin, Dylan R., McKenna, Aaron, Camp, Nathan D., Srivastava, Saurabh, MacGilvray, Matthew E., Bodík, Rastislav, Wolf-Yadlin, Alejandro, Fraenkel, Ernest, Fisher, Jasmin, Gitter, Anthony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6295338/
https://www.ncbi.nlm.nih.gov/pubmed/30257219
http://dx.doi.org/10.1016/j.celrep.2018.08.085
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author Kӧksal, Ali Sinan
Beck, Kirsten
Cronin, Dylan R.
McKenna, Aaron
Camp, Nathan D.
Srivastava, Saurabh
MacGilvray, Matthew E.
Bodík, Rastislav
Wolf-Yadlin, Alejandro
Fraenkel, Ernest
Fisher, Jasmin
Gitter, Anthony
author_facet Kӧksal, Ali Sinan
Beck, Kirsten
Cronin, Dylan R.
McKenna, Aaron
Camp, Nathan D.
Srivastava, Saurabh
MacGilvray, Matthew E.
Bodík, Rastislav
Wolf-Yadlin, Alejandro
Fraenkel, Ernest
Fisher, Jasmin
Gitter, Anthony
author_sort Kӧksal, Ali Sinan
collection PubMed
description We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It systematically eliminates all candidate structures for a signaling pathway where a protein is activated or inactivated before its upstream regulators. The algorithm can model more than one hundred thousand dynamic phosphosites and can discover pathway members that are not differentially phosphorylated. By analyzing temporal data, TPS defines signaling cascades without needing to experimentally perturb individual proteins. It recovers known pathways and proposes pathway connections when applied to the human epidermal growth factor and yeast osmotic stress responses. Independent kinase mutant studies validate predicted substrates in the TPS osmotic stress pathway.
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spelling pubmed-62953382018-12-16 Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data Kӧksal, Ali Sinan Beck, Kirsten Cronin, Dylan R. McKenna, Aaron Camp, Nathan D. Srivastava, Saurabh MacGilvray, Matthew E. Bodík, Rastislav Wolf-Yadlin, Alejandro Fraenkel, Ernest Fisher, Jasmin Gitter, Anthony Cell Rep Article We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It systematically eliminates all candidate structures for a signaling pathway where a protein is activated or inactivated before its upstream regulators. The algorithm can model more than one hundred thousand dynamic phosphosites and can discover pathway members that are not differentially phosphorylated. By analyzing temporal data, TPS defines signaling cascades without needing to experimentally perturb individual proteins. It recovers known pathways and proposes pathway connections when applied to the human epidermal growth factor and yeast osmotic stress responses. Independent kinase mutant studies validate predicted substrates in the TPS osmotic stress pathway. 2018-09-25 /pmc/articles/PMC6295338/ /pubmed/30257219 http://dx.doi.org/10.1016/j.celrep.2018.08.085 Text en This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kӧksal, Ali Sinan
Beck, Kirsten
Cronin, Dylan R.
McKenna, Aaron
Camp, Nathan D.
Srivastava, Saurabh
MacGilvray, Matthew E.
Bodík, Rastislav
Wolf-Yadlin, Alejandro
Fraenkel, Ernest
Fisher, Jasmin
Gitter, Anthony
Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data
title Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data
title_full Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data
title_fullStr Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data
title_full_unstemmed Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data
title_short Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data
title_sort synthesizing signaling pathways from temporal phosphoproteomic data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6295338/
https://www.ncbi.nlm.nih.gov/pubmed/30257219
http://dx.doi.org/10.1016/j.celrep.2018.08.085
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