dc.contributor.author
Knöchel, Jane
dc.contributor.author
Kloft, Charlotte
dc.contributor.author
Huisinga, Wilhelm
dc.date.accessioned
2024-03-12T09:50:44Z
dc.date.available
2024-03-12T09:50:44Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/42768
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-42484
dc.description.abstract
In systems biology and pharmacology, large-scale kinetic models are used to study the dynamic response of a system to a specific input or stimulus. While in many applications, a deeper understanding of the input-response behaviour is highly desirable, it is often hindered by the large number of molecular species and the complexity of the interactions. An approach that identifies key molecular species for a given input-response relationship and characterises dynamic properties of states is therefore highly desirable. We introduce the concept of index analysis; it is based on different time- and state-dependent quantities (indices) to identify important dynamic characteristics of molecular species. All indices are defined for a specific pair of input and response variables as well as for a specific magnitude of the input. In application to a large-scale kinetic model of the EGFR signalling cascade, we identified different phases of signal transduction, the peculiar role of Phosphatase3 during signal activation and Ras recycling during signal onset. In addition, we discuss the challenges and pitfalls of interpreting the relevance of molecular species based on knock-out simulation studies, and provide an alternative view on conflicting results on the importance of parallel EGFR downstream pathways. Beyond the applications in model interpretation, index analysis is envisioned to be a valuable tool in model reduction.
en
dc.format.extent
27 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Signaling networks
en
dc.subject
Signaling cascades
en
dc.subject
EGFR signaling
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie
dc.title
Index analysis: An approach to understand signal transduction with application to the EGFR signalling pathway
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
e1011777
dcterms.bibliographicCitation.doi
10.1371/journal.pcbi.1011777
dcterms.bibliographicCitation.journaltitle
PLOS Computational Biology
dcterms.bibliographicCitation.number
2
dcterms.bibliographicCitation.volume
20
dcterms.bibliographicCitation.url
https://doi.org/10.1371/journal.pcbi.1011777
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Pharmazie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1553-7358
refubium.resourceType.provider
WoS-Alert