nach oben

Erschienen in:

2016 | OriginalPaper | Buchkapitel

On Observability and Reconstruction of Promoter Activity Statistics from Reporter Protein Mean and Variance Profiles

verfasst von : Eugenio Cinquemani

Erschienen in: Hybrid Systems Biology

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Reporter protein systems are widely used in biology for the indirect quantitative monitoring of gene expression activity over time. At the level of population averages, the relationship between the observed reporter concentration profile and gene promoter activity is established, and effective methods have been introduced to reconstruct this information from the data. At single-cell level, the relationship between population distribution time profiles and the statistics of promoter activation is still not fully investigated, and adequate reconstruction methods are lacking.

This paper develops new results for the reconstruction of promoter activity statistics from mean and variance profiles of a reporter protein. Based on stochastic modelling of gene expression dynamics, it discusses the observability of mean and autocovariance function of an arbitrary random binary promoter activity process. Mathematical relationships developed are explicit and nonparametric, i.e. free of a priori assumptions on the laws governing the promoter process, thus allowing for the decoupled analysis of the switching dynamics in a subsequent step. The results of this work constitute the essential tools for the development of promoter statistics and regulatory mechanism inference algorithms.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Discrete Abstraction of Multiaffine Systems

Nächstes Kapitel Logic-Based Multi-objective Design of Chemical Reaction Networks

Nur mit Berechtigung zugänglich

Bowsher, C.G., Voliotis, M., Swain, P.S.: The fidelity of dynamic signaling by noisy biomolecular networks. PLoS Comput. Biol. 9(3), e1002965 (2013)MathSciNetCrossRef

Cinquemani, E.: Reconstruction of promoter activity statistics from reporter protein population snapshot data. In: 2015 54th IEEE Conference on Decision and Control (CDC), pp. 1471–1476, December 2015

Cinquemani, E.: Reconstructing statistics of promoter switching from reporter protein population snapshot data. In: Abate, A., et al. (eds.) HSB 2015. LNCS, vol. 9271, pp. 3–19. Springer, Heidelberg (2015). doi:10.1007/978-3-319-26916-0_1 CrossRef

De Nicolao, G., Sparacino, G., Cobelli, C.: Nonparametric input estimation in physiological systems: problems, methods, and case studies. Automatica 33(5), 851–870 (1997)MathSciNetCrossRefMATH

Friedman, N., Cai, L., Xie, X.S.: Linking stochastic dynamics to population distribution: an analytical framework of gene expression. Phys. Rev. Lett. 97, 168302 (2006)CrossRef

Hasenauer, J., Waldherr, S., Doszczak, M., Radde, N., Scheurich, P., Allgower, F.: Identification of models of heterogeneous cell populations from population snapshot data. BMC Bioinform. 12(1), 125 (2011)CrossRefMATH

Hasenauer, J., Wolf, V., Kazeroonian, A., Theis, F.J.: Method of conditional moments (MCM) for the chemical master equation. J. Math. Biol. 69(3), 687–735 (2014)MathSciNetCrossRefMATH

Hespanha, J.: Modelling and analysis of stochastic hybrid systems. IEE Proc. Control Theor. Appl. 153(5), 520–535 (2006)MathSciNetCrossRef

de Jong, H., Ranquet, C., Ropers, D., Pinel, C., Geiselmann, J.: Experimental and computational validation of models of fluorescent and luminescent reporter genes in bacteria. BMC Syst. Biol. 4(1), 55 (2010)CrossRef

10.

Kaern, M., Elston, T.C., Blake, W.J., Collins, J.J.: Stochasticity in gene expression: from theories to phenotypes. Nat. Rev. Gen. 6, 451–464 (2005)CrossRef

11.

Koopmans, L.H.: The Spectral Analysis of Time Series. Probability and Mathematical Statistics. Academic Press, San Diego (1995)MATH

12.

Lindquist, A., Picci, G.: Linear Stochastic Systems - A Geometric Approach to Modeling, Estimation and Identification. Springer, Heidelberg (2015)MATH

13.

Munsky, B., Trinh, B., Khammash, M.: Listening to the noise: Random fluctuations reveal gene network parameters. Mol. Syst. Biol. 5 (2009). Article ID 318

14.

Neuert, G., Munsky, B., Tan, R., Teytelman, L., Khammash, M., van Oudenaarden, A.: Systematic identification of signal-activated stochastic gene regulation. Science 339(6119), 584–587 (2013)CrossRef

15.

Papoulis, A.: Probability, Random Variables, and Stochastic Processes. McGraw-Hill Series in Electrical Engineering. McGraw-Hill, New York (1991)MATH

16.

Paulsson, J.: Models of stochastic gene expression. Phys. Life Rev. 2(2), 157–175 (2005)CrossRef

17.

Sanft, K.R., Wu, S., Roh, M., Fu, J., Lim, R.K., Petzold, L.R.: Stochkit2: Software for discrete stochastic simulation of biochemical systems with events. Bioinformatics 27(17), 2457–2458 (2011)CrossRef

18.

Stefan, D., Pinel, C., Pinhal, S., Cinquemani, E., Geiselmann, J., de Jong, H.: Inference of quantitative models of bacterial promoters from time-series reporter gene data. PLoS Comput. Biol. 11(1), e1004028 (2015)CrossRef

19.

Zechner, C., Ruess, J., Krenn, P., Pelet, S., Peter, M., Lygeros, J., Koeppl, H.: Moment-based inference predicts bimodality in transient gene expression. PNAS 21(109), 8340–8345 (2012)CrossRef

20.

Zechner, C., Unger, M., Pelet, S., Peter, M., Koeppl, H.: Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings. Nat. Methods 11, 197–202 (2014)CrossRef

21.

Zulkower, V., Page, M., Ropers, D., Geiselmann, J., de Jong, H.: Robust reconstruction of gene expression profiles from reporter gene data using linear inversion. Bioinformatics 31(12), i71–i79 (2015)CrossRef

Titel: On Observability and Reconstruction of Promoter Activity Statistics from Reporter Protein Mean and Variance Profiles
verfasst von: Eugenio Cinquemani
Verlag: Springer International Publishing
Buch: Hybrid Systems Biology
Print ISBN: 978-3-319-47150-1

Electronic ISBN: 978-3-319-47151-8

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-47151-8_10

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner