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Analyzing causal relationships in proteomic profiles using CausalPath

CausalPath (causalpath.org) evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic...

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Detalles Bibliográficos
Autores principales: Luna, Augustin, Siper, Metin Can, Korkut, Anil, Durupinar, Funda, Dogrusoz, Ugur, Aslan, Joseph E., Sander, Chris, Demir, Emek, Babur, Ozgun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633371/
https://www.ncbi.nlm.nih.gov/pubmed/34877547
http://dx.doi.org/10.1016/j.xpro.2021.100955
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author Luna, Augustin
Siper, Metin Can
Korkut, Anil
Durupinar, Funda
Dogrusoz, Ugur
Aslan, Joseph E.
Sander, Chris
Demir, Emek
Babur, Ozgun
author_facet Luna, Augustin
Siper, Metin Can
Korkut, Anil
Durupinar, Funda
Dogrusoz, Ugur
Aslan, Joseph E.
Sander, Chris
Demir, Emek
Babur, Ozgun
author_sort Luna, Augustin
collection PubMed
description CausalPath (causalpath.org) evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic features, which are called prior relations. The subset of the prior relations that are supported by the proteomic profiles are reported and evaluated for statistical significance. The end result is a network model of signaling that explains the patterns observed in the experimental dataset. For complete details on the use and execution of this protocol, please refer to Babur et al. (2021).
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spelling pubmed-86333712021-12-06 Analyzing causal relationships in proteomic profiles using CausalPath Luna, Augustin Siper, Metin Can Korkut, Anil Durupinar, Funda Dogrusoz, Ugur Aslan, Joseph E. Sander, Chris Demir, Emek Babur, Ozgun STAR Protoc Protocol CausalPath (causalpath.org) evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic features, which are called prior relations. The subset of the prior relations that are supported by the proteomic profiles are reported and evaluated for statistical significance. The end result is a network model of signaling that explains the patterns observed in the experimental dataset. For complete details on the use and execution of this protocol, please refer to Babur et al. (2021). Elsevier 2021-11-23 /pmc/articles/PMC8633371/ /pubmed/34877547 http://dx.doi.org/10.1016/j.xpro.2021.100955 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Protocol
Luna, Augustin
Siper, Metin Can
Korkut, Anil
Durupinar, Funda
Dogrusoz, Ugur
Aslan, Joseph E.
Sander, Chris
Demir, Emek
Babur, Ozgun
Analyzing causal relationships in proteomic profiles using CausalPath
title Analyzing causal relationships in proteomic profiles using CausalPath
title_full Analyzing causal relationships in proteomic profiles using CausalPath
title_fullStr Analyzing causal relationships in proteomic profiles using CausalPath
title_full_unstemmed Analyzing causal relationships in proteomic profiles using CausalPath
title_short Analyzing causal relationships in proteomic profiles using CausalPath
title_sort analyzing causal relationships in proteomic profiles using causalpath
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633371/
https://www.ncbi.nlm.nih.gov/pubmed/34877547
http://dx.doi.org/10.1016/j.xpro.2021.100955
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