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Reconstruction of promoter activity statistics from reporter protein population snapshot data

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Abstract:
The use of fluorescent reporter proteins is an established experimental approach for dynamic quantification of gene expression over time. Yet, the observed fluorescence levels are only indirect measurements of the relevant promoter activity. At the level of population averages, reconstruction of mean activity profiles from mean fluorescence profiles has been addressed with satisfactory results. At the single cell level, however, promoter activity is generally different from cell to cell. Making sense of this variability is at the core of single-cell modelling, but complicates the reconstruction task. We will discuss reconstruction of promoter activity statistics from time-lapse population snapshots of fluorescent reporter statistics, as obtained e.g. by flow-cytometric measurements of a dynamical gene expression experiment. Based on a stochastic modelling framework, we will consider the problem in terms of identification and in terms of dynamical estimation. We will first develop a theoretical investigation of structural and practical identifiability of the typically unknown reporter protein kinetic parameters in presence of random promoter activation. Then, for known kinetic parameters, we will present parametric and nonparametric approaches to the reconstruction of unknown promoter statistics. Demonstration of these methods will be provided based on relevant in-silico examples.

Type of Seminar:
IfA Seminar
Speaker:
Dr. Eugenio Cinquemani
INRIA Grenoble – Rhône - Alpes, France
Date/Time:
Jan 27, 2016   3.00 pm
Location:

ETZ E 7
Contact Person:

Prof. John Lygeros
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Biographical Sketch:
Eugenio Cinquemani received the Laurea degree in 2001 and the Ph.D. degree in 2005 from the Department of Information Engineering of the University of Padova, Italy. His formation included a 1-year visit at the University of California - Berkeley on a student exchange program. From 2006 to 2009 he has been working as a Post-Doc at the Automatic Control Laboratory of the ETH Zurich, Switzerland. In November 2009 he was appointed Research Scientist at INRIA Grenoble - Rhône-Alpes, France, where he is currently working in the computational biology and bioinformatics project-team IBIS. His research interests are currently focused on modelling, identification and estimation of biochemical interaction network dynamics from experimental data, and also include identification, estimation and control methods for stochastic and hybrid systems.