Change search
ReferencesLink to record
Permanent link

Direct link
In silico labeling reveals the time-dependent label half-life and transit-time in dynamical systems
Centre Syst Biol, Germany Harvard University, MA USA .
University Hospital, Germany Harvard University, MA USA .
Centre Syst Biol, Germany .
Centre Syst Biol, Germany .
Show others and affiliations
2012 (English)In: BMC Systems Biology, ISSN 1752-0509, Vol. 6, no 13Article in journal (Refereed) Published
Abstract [en]

Background: Mathematical models of dynamical systems facilitate the computation of characteristic properties that are not accessible experimentally. In cell biology, two main properties of interest are (1) the time-period a protein is accessible to other molecules in a certain state - its half-life - and (2) the time it spends when passing through a subsystem - its transit-time. We discuss two approaches to quantify the half-life, present the novel method of in silico labeling, and introduce the label half-life and label transit-time. The developed method has been motivated by laboratory tracer experiments. To investigate the kinetic properties and behavior of a substance of interest, we computationally label this species in order to track it throughout its life cycle. The corresponding mathematical model is extended by an additional set of reactions for the labeled species, avoiding any double-counting within closed circuits, correcting for the influences of upstream fluxes, and taking into account combinatorial multiplicity for complexes or reactions with several reactants or products. A profile likelihood approach is used to estimate confidence intervals on the label half-life and transit-time. Results: Application to the JAK-STAT signaling pathway in Epo-stimulated BaF3-EpoR cells enabled the calculation of the time-dependent label half-life and transit-time of STAT species. The results were robust against parameter uncertainties. Conclusions: Our approach renders possible the estimation of species and label half-lives and transit-times. It is applicable to large non-linear systems and an implementation is provided within the PottersWheel modeling framework (

Place, publisher, year, edition, pages
BioMed Central , 2012. Vol. 6, no 13
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-79834DOI: 10.1186/1752-0509-6-13ISI: 000305621400001OAI: diva2:544389
Available from: 2012-08-14 Created: 2012-08-14 Last updated: 2012-10-19

Open Access in DiVA

fulltext(1421 kB)124 downloads
File information
File name FULLTEXT01.pdfFile size 1421 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Timmer, Jens
By organisation
Cell BiologyFaculty of Health Sciences
In the same journal
BMC Systems Biology
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 124 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 38 hits
ReferencesLink to record
Permanent link

Direct link