PMID- 21406095
OWN - NLM
STAT- MEDLINE
DCOM- 20110624
LR  - 20211020
IS  - 1752-0509 (Electronic)
IS  - 1752-0509 (Linking)
VI  - 5
DP  - 2011 Mar 15
TI  - Understanding dynamics using sensitivity analysis: caveat and solution.
PG  - 41
LID - 10.1186/1752-0509-5-41 [doi]
AB  - BACKGROUND: Parametric sensitivity analysis (PSA) has become one of the most 
      commonly used tools in computational systems biology, in which the sensitivity 
      coefficients are used to study the parametric dependence of biological models. As 
      many of these models describe dynamical behaviour of biological systems, the PSA 
      has subsequently been used to elucidate important cellular processes that 
      regulate this dynamics. However, in this paper, we show that the PSA coefficients 
      are not suitable in inferring the mechanisms by which dynamical behaviour arises 
      and in fact it can even lead to incorrect conclusions. RESULTS: A careful 
      interpretation of parametric perturbations used in the PSA is presented here to 
      explain the issue of using this analysis in inferring dynamics. In short, the PSA 
      coefficients quantify the integrated change in the system behaviour due to 
      persistent parametric perturbations, and thus the dynamical information of when a 
      parameter perturbation matters is lost. To get around this issue, we present a 
      new sensitivity analysis based on impulse perturbations on system parameters, 
      which is named impulse parametric sensitivity analysis (iPSA). The inability of 
      PSA and the efficacy of iPSA in revealing mechanistic information of a dynamical 
      system are illustrated using two examples involving switch activation. 
      CONCLUSIONS: The interpretation of the PSA coefficients of dynamical systems 
      should take into account the persistent nature of parametric perturbations 
      involved in the derivation of this analysis. The application of PSA to identify 
      the controlling mechanism of dynamical behaviour can be misleading. By using 
      impulse perturbations, introduced at different times, the iPSA provides the 
      necessary information to understand how dynamics is achieved, i.e. which 
      parameters are essential and when they become important.
FAU - Perumal, Thanneer M
AU  - Perumal TM
AD  - Department of Chemical and Biomolecular Engineering, National University of 
      Singapore, Singapore.
FAU - Gunawan, Rudiyanto
AU  - Gunawan R
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20110315
PL  - England
TA  - BMC Syst Biol
JT  - BMC systems biology
JID - 101301827
SB  - IM
MH  - Cell Death/physiology
MH  - Computational Biology/*methods
MH  - Humans
MH  - Jurkat Cells
MH  - Kinetics
MH  - *Models, Biological
MH  - Molecular Dynamics Simulation
MH  - Systems Biology/*methods
PMC - PMC3070647
EDAT- 2011/03/17 06:00
MHDA- 2011/06/28 06:00
PMCR- 2011/03/15
CRDT- 2011/03/17 06:00
PHST- 2010/09/24 00:00 [received]
PHST- 2011/03/15 00:00 [accepted]
PHST- 2011/03/17 06:00 [entrez]
PHST- 2011/03/17 06:00 [pubmed]
PHST- 2011/06/28 06:00 [medline]
PHST- 2011/03/15 00:00 [pmc-release]
AID - 1752-0509-5-41 [pii]
AID - 10.1186/1752-0509-5-41 [doi]
PST - epublish
SO  - BMC Syst Biol. 2011 Mar 15;5:41. doi: 10.1186/1752-0509-5-41.