Cargando…

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...

Descripción completa

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
Descripción
Sumario: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).