Zechner, C. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2011)
Recursive Bayesian estimation of stochastic rate constants from heterogeneous cell populations.
In: IEEE Conference on Decision and Control and European Control Conference
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Robust estimation of kinetic parameters of intracellular processes requires large amounts of quantitative data. Due to the high uncertainty of such processes and the fact that recent single-cell measurement techniques have limited resolution and dimensionality, estimation should pool recordings of multiple cells of an isogenic cell population. However, experimental results have shown that several factors such as cell volume or cell-cycle stage can drastically affect signaling as well as protein expression, leading to inherent heterogeneities in the cell population measurements. Here we present a recursive Bayesian estimation procedure for stochastic kinetic model calibration using heterogeneous cell population data. While obtaining optimal estimates for the rate constants, this approach allows to reconstruct missing species as well as to quantitatively capture extrinsic variability. The proposed algorithm is applied to a model of the osmo-stress induced MAPK Hog1 activation in the cytoplasm and its translocation to the nucleus.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2011 |
| Autor(en): | Zechner, C. ; Pelet, S. ; Peter, M. ; Koeppl, H. |
| Art des Eintrags: | Bibliographie |
| Titel: | Recursive Bayesian estimation of stochastic rate constants from heterogeneous cell populations |
| Sprache: | Deutsch |
| Publikationsjahr: | Dezember 2011 |
| Ort: | Orlando, Florida |
| Verlag: | IEEE |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Conference on Decision and Control and European Control Conference |
| URL / URN: | http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe... |
| Kurzbeschreibung (Abstract): | Robust estimation of kinetic parameters of intracellular processes requires large amounts of quantitative data. Due to the high uncertainty of such processes and the fact that recent single-cell measurement techniques have limited resolution and dimensionality, estimation should pool recordings of multiple cells of an isogenic cell population. However, experimental results have shown that several factors such as cell volume or cell-cycle stage can drastically affect signaling as well as protein expression, leading to inherent heterogeneities in the cell population measurements. Here we present a recursive Bayesian estimation procedure for stochastic kinetic model calibration using heterogeneous cell population data. While obtaining optimal estimates for the rate constants, this approach allows to reconstruct missing species as well as to quantitatively capture extrinsic variability. The proposed algorithm is applied to a model of the osmo-stress induced MAPK Hog1 activation in the cytoplasm and its translocation to the nucleus. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Bioinspirierte Kommunikationssysteme 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik |
| Hinterlegungsdatum: | 04 Apr 2014 11:41 |
| Letzte Änderung: | 23 Sep 2021 14:32 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum