Dr Bärbel Finkenstädt (MSc Course Tutor and MSc Admissions)

Contact me at: b.f.finkenstadt 'at' warwick.ac.uk

OFFICE HOURS

TERM 3, Week 3-8 : Tues 10:00-11:00, Wedn 14:30-15:30

TERM 3, Week 9-10: End of term tutorial times will be posted nearer in time (ALL personal tutees required to attend)

Telephone: 024 7657 2580

Teaching Term 1: ST952 Introduction to Statistical Practise

Research Interests

My area of research is in statistics and mathematical biology. In particular, I am interested in the analysis of time series and stochastic processes and their connection to the theory of dynamical systems in biology. These are typically systems that can be described by stochastic or ordinary differential equations. In the past I have mainly worked on research problems in population ecology and epidemiology. More recently I have been focusing on molecular biology. There are many interesting statistical challenges in linking these sciences to real data.

I am collaborating with biologists, mathematicians and bioinformaticians at Warwick, Liverpool and Edinburgh System Biology Centres in studying the molecular dynamics of oscillating molecular systems such as circadian clocks, NF-kappa-B, and other regulatory networks of genes. I am particularly interested in statistical inference about important kinetic parameters as well as the modeling of the system itself. Interesting statistical research questions are the reconstruction of time profiles for gene transcription from time series data on proteins of reporter genes, estimation of kinetic parameters such as degradation rates/halflives of proteins and mRNA molecules and the modelling of times when gene are more or less active. The relevant statistical methodologies involve, for example, dealing with unobserved processes, identifiability of parameters, inference for processes modeled by nonlinear (stochastic or deterministic) differential equations, Bayesian hierarchical modelling, Markov chain Monte Carlo estimation, multiple switch-point modelling using RJMCMC, robust period estimation for circadian data using Bootstrapping methods, etc. My collaborators on these topics are Maria Costa, Dan Woodcock, Dafyd Jenkins and Siren Veflinstad (postdoctoral researchers at WSB and Stats), Michal Komorowski, David Rand (WSB), Isabelle Carre (Warwick Biology) and various other scientists involved in the following large interdisciplinary SABR (System Approaches to Biologal Research) projects funded by BBSRC:

PRESTA: Plant Responses to Environmental STress in Arabidopsis

ROBuST (Regulation of Biological signalling by temperature)

Dynamics and function of the NF-kappaB signalling system

Publications (since 2005)

Rittman M, Hoffmann SV, Gilroy E, Hicks MR, Finkenstädt B, Rodger A (2012) Probing the structure of long DNA molecules in solution using synchrotron radiation linear dichroism. Physical Chemistry Chemical Physics (Phys. Chem. Chem. Phys.), 2012, DOI: 10.1039/C1CP22371B, http://xlink.rsc.org/?doi=C1CP22371B

Harper CV, Finkenstädt B, Woodcock DJ, Friedrichsen S, Semprini S, et al. (2011) Dynamic Analysis of Stochastic Transcription Cycles. PLoS Biology 9(4): e1000607. doi:10.1371/journal.pbio.1000607

Ferreira, M., Finkenstädt , B., Oliveira, B.M.P.M., Pinto, Alberto A. and A.N. Yannacopoulos, (2011), On the convergence to Walrasian prices in random matching Edgeworthian economies, to appear in Central European Journal of Operations Research.

Ferreira, M., Finkenstädt , B., Oliveira, B.M.P.M., Pinto, Alberto A. and A.N. Yannacopoulos, (2011), A modified model of an Edgeworthian Economy, in Dynamics, Games and Science I (eds. M.M. Peixoto et al.), Springer Proceedings in Mathematics, DOI 10.1007/978-3-642-11456-4_21, Springer Verlag, Berlin Heidelberg 2011.

Komorowski, M. , Finkenstädt , B., Rand, D. A. , (2010); Using single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression, Biophysical Journal, Vol 98, Issue 12, 2759-2769, online at http://www.cell.com/biophysj/

Komorowski, M. , Finkenstädt , B., Harper, C. V., Rand, D. A. , (2009); Bayesian inference of biochemical kinetic parameters using the linear noise approximation, BMC Bioinformatics, 2009, 10:343 doi:10.1186/1471-2105-10-343, 2009, online at: http://www.biomedcentral.com/1471-2105/10/343

B. Finkenstadt; E. A. Heron; M. Komorowski; K. Edwards; S. Tang; C. V. Harper; J. R. E. Davis; M. R. H. White; A. J. Millar; D. A. Rand, (2008); Reconstruction of transcriptional dynamics from gene reporter data using differential equations, Bioinformatics, 2008; 24: 2901 - 2907.

Heron, E., Finkenstädt, B. F. and Rand, D.A., (2007), Bayesian Inference for dynamic transcriptional regulation; the Hes1 system as a case study. Bioinformatics, 23 (19), 2589-2595.

Lekone, P.E. and Finkenstädt, B. F., (2006), Statistical Inference in a stochastic epidemic SEIR model with control intervention: Ebola as a case study. Biometrics, 2006 (62), 1170-1177.

Finkenstädt, B. F. , Held L. and Isham, V. (eds), 2006, Statistical Methods for Spatio-temporal systems, CRC Press/Chapman and Hall.

Finkenstädt, B. F., Morton, A.M and Rand, D. A. (2005), Modelling antigenic drift in weekly flu incidence. Statistics in Medicine, 2005 (24), 3447-3461.

Morton, A.M. and Finkenstädt, B. F. (2005) Discrete-time modelling of disease incidence time series by using Markov Chain Monte Carlo methods, J. R. Statist. Soc. C., Applied Statistics, 54 (3), 575-594.