Calibration or model parameter estimation from measured data is an ubiquitous problem in engineering. In systems biology this problem turns out to be particularly challenging due to very short data-records, low signal-to-noise ratio of data acquisition, large intrinsic process noise and limited measurement access to only a few, of sometimes several hundreds, state variables. We review state-of-the-art model calibration techniques and also discuss their relation to the general reverseengineering problem in systems biology. For biomolecular circuits involving low-copy-number molecules we adopt a Markov process setup and discuss a calibration approach based on suitable metrics between probability measures and propose the metrics computation for the multivariate case. In particular, we use Kantorovich's distance and devise an algorithm, for the case when FACS (fluorescence-activated cell sorting) measurements are given. We discuss a case study involving FACS data for the high-osmolarity glycerol (HOG) pathway in budding yeast.

Probability metrics to calibrate stochastic chemical kinetics

SETTI, Gianluca;
2010

Abstract

Calibration or model parameter estimation from measured data is an ubiquitous problem in engineering. In systems biology this problem turns out to be particularly challenging due to very short data-records, low signal-to-noise ratio of data acquisition, large intrinsic process noise and limited measurement access to only a few, of sometimes several hundreds, state variables. We review state-of-the-art model calibration techniques and also discuss their relation to the general reverseengineering problem in systems biology. For biomolecular circuits involving low-copy-number molecules we adopt a Markov process setup and discuss a calibration approach based on suitable metrics between probability measures and propose the metrics computation for the multivariate case. In particular, we use Kantorovich's distance and devise an algorithm, for the case when FACS (fluorescence-activated cell sorting) measurements are given. We discuss a case study involving FACS data for the high-osmolarity glycerol (HOG) pathway in budding yeast.
2010
9781424453085
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1395176
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact