A comparison of mechanistic signaling pathway activity analysis methods. (3rd June 2018)

• Record Type: Journal Article
• Authors: Amadoz, Alicia; Hidalgo, Marta R; Çubuk, Cankut; Carbonell-Caballero, José; Dopazo, Joaquín
• Is Part Of: Briefings in bioinformatics. Volume 20:Number 5(2020)
• Page Start: 1655
• Page End: 1668
• Publication Date: 2018-06-03
• Subjects: systems biology -- mathematical models -- signaling pathways -- disease mechanism -- transcriptomics -- networks; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby040
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Understanding the aspects of cell functionality that account for disease mechanisms or drug modes of action is a main challenge for precision medicine. Classical gene-based approaches ignore the modular nature of most human traits, whereas conventional pathway enrichment approaches produce only illustrative results of limited practical utility. Recently, a family of new methods has emerged that change the focus from the whole pathways to the definition of elementary subpathways within them that have any mechanistic significance and to the study of their activities. Thus, mechanistic pathway activity (MPA) methods constitute a new paradigm that allows recoding poorly informative genomic measurements into cell activity quantitative values and relate them to phenotypes. Here we provide a review on the MPA methods available and explain their contribution to systems medicine approaches for addressing challenges in the diagnostic and treatment of complex diseases.