From expression footprints to causal pathways

• Verfasst von: Liu, Anika [VerfasserIn]
• Verfasst von: Trairatphisan, Panuwat [VerfasserIn]
• Verfasst von: Gjerga, Enio [VerfasserIn]
• Verfasst von: Sáez Rodríguez, Julio [VerfasserIn]
• Titel: From expression footprints to causal pathways
• Titelzusatz: contextualizing large signaling networks with CARNIVAL
• Verf.angabe: Anika Liu, Panuwat Trairatphisan, Enio Gjerga, Athanasios Didangelos, Jonathan Barratt and Julio Saez-Rodriguez
• E-Jahr: 2019
• Jahr: 11 November 2019
• Umfang: 10 S.
• Fussnoten: Gesehen am 30.03.2020 ; Anika Liu, Panuwat Trairatphisan and Enio Gjerga contributed equally
• Titel Quelle: Enthalten in: npj Systems biology and applications
• Ort Quelle: London : Nature Publ. Group, 2015
• Jahr Quelle: 2019
• Band/Heft Quelle: 5(2019,1) Artikel- Nummer 40, 10 Seiten
• ISSN Quelle: 2056-7189
• DOI: doi:10.1038/s41540-019-0118-z
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1693480484

Abstract

Changes in gene expression are generally indirect consequences of upstream dysregulation, and it is often important to understand what caused it. A team of researchers led by Julio Saez-Rodriguez from Heidelberg and Aachen has developed CARNIVAL to infer causal networks of proteins upstream of gene expression. In the first step, dysregulated transcription factors are inferred from gene expression. Subsequently, an algorithm finds explanations for their up- or down-regulation through known protein-protein interactions using an ILP formulation. Optionally, known targets of perturbation can be provided. This integration of different sources of prior knowledge led to higher performance than alternative methods and was able to identify key pathways and proteins, including TGFβ signaling and β-Catenin, in a case study on IgA nephropathy. Overall, CARNIVAL may provide clues to understand causal mechanisms in diseases and treatments.