Improving data fitting of a signal transduction model by global sensitivity analysis

Y. Jin, H. Yue, M. Brown, Y. Liang, D.B. Kell

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

15 Citations (Scopus)

Abstract

Based on a simplified model of the (TNF-α mediated) IκBα-NF-κB signal transduction pathway, global sensitivity analysis has been performed to identify those parameters that exert significant control on the system outputs. The permutation operation in Morris method is modified to work for log-uniform sampling parameters. The identified sensitive parameters are then estimated using multivariable search such that the output of the model matches experimental data representing the nuclear concentration of NF-κB. Such
parameter tuning leads to much better agreement between the model and the experimental time series relative to those previously published. This shows the importance of global sensitivity analysis in Systems Biology models
Original languageEnglish
Title of host publicationProceedings of the 2007 American Control Conference
Pages2708-2713
Number of pages6
Publication statusPublished - 2007
EventAmerican Control Conference - , United Kingdom
Duration: 5 Jul 2007 → …

Conference

ConferenceAmerican Control Conference
CountryUnited Kingdom
Period5/07/07 → …

Fingerprint

sensitivity analysis
time series
sampling
parameter

Keywords

  • signal transduction
  • global sensitivity analysis

Cite this

Jin, Y., Yue, H., Brown, M., Liang, Y., & Kell, D. B. (2007). Improving data fitting of a signal transduction model by global sensitivity analysis. In Proceedings of the 2007 American Control Conference (pp. 2708-2713)
Jin, Y. ; Yue, H. ; Brown, M. ; Liang, Y. ; Kell, D.B. / Improving data fitting of a signal transduction model by global sensitivity analysis. Proceedings of the 2007 American Control Conference. 2007. pp. 2708-2713
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Jin, Y, Yue, H, Brown, M, Liang, Y & Kell, DB 2007, Improving data fitting of a signal transduction model by global sensitivity analysis. in Proceedings of the 2007 American Control Conference. pp. 2708-2713, American Control Conference, United Kingdom, 5/07/07.

Improving data fitting of a signal transduction model by global sensitivity analysis. / Jin, Y.; Yue, H.; Brown, M.; Liang, Y.; Kell, D.B.

Proceedings of the 2007 American Control Conference. 2007. p. 2708-2713.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N2 - Based on a simplified model of the (TNF-α mediated) IκBα-NF-κB signal transduction pathway, global sensitivity analysis has been performed to identify those parameters that exert significant control on the system outputs. The permutation operation in Morris method is modified to work for log-uniform sampling parameters. The identified sensitive parameters are then estimated using multivariable search such that the output of the model matches experimental data representing the nuclear concentration of NF-κB. Suchparameter tuning leads to much better agreement between the model and the experimental time series relative to those previously published. This shows the importance of global sensitivity analysis in Systems Biology models

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Jin Y, Yue H, Brown M, Liang Y, Kell DB. Improving data fitting of a signal transduction model by global sensitivity analysis. In Proceedings of the 2007 American Control Conference. 2007. p. 2708-2713