Dr Bärbel Finkenstädt (PhD Director)
Office hours for Academic year 2014/15, term 1:
Beginning of term tutorials (first 2 weeks of term) All personal tutees required to attend in fulfillment of monitoring points (no need to sign up at my door): Wedn 1/10 8:30-10:00, Fri 3/10 14:30-16:30, Mo 6/10 8:30-10:00, Wedn 8/10 8:30-10:00.
Please note: I cannot do office hour on 27 and 29 October. In urgent cases please see Julia Brettschneider.
Regular office hours (from week 3): Mondays 8:30-9:30, Wednesdays 8:30-9:30
email: Barbel.Finkenstadt 'at' warwick.ac.uk
Telephone: 024 7657 2580
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. 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 of kinetic parameters from experimental data. 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 George Minas, Dan Woodcock, Dafyd Jenkins (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:
ROBuST (Regulation of Biological signalling by temperature)
Some recent publications
Sidaway-Lee, K., Costa, M.J., Rand, D.A., Finkenstädt, B. and Penfield, S. (2014), Direct measurement of transcription rates reveals multiple mechanisms for configuration of the Arabidopsis ambient temperature response, to appear in Genome Biology
Finkenstädt , B., Woodcock, D.J., Komorowski, M. , Harper, C.V., Davis, J.R.E., White, M.R.H., Rand, D. A., (2013), Quantifying intrinsic and extrinsic noise in gene transcription using the linear noise approximation: an application to single cell data, Annals of Applied Statistics 2013, Vol. 7, No. 4, 1960–1982.
Costa M.J., Finkenstädt, B., Gould, P.D, Foreman, J., Halliday, K., Hall, A., Roche, V., Levi, F. and Rand, D.A., (2013), Inference on periodicity of circadian time series, Biostatistics 2013, 14(4):792-806. doi: 10.1093/biostatistics/kxt020.
Woodcock, DJ, Vance KW, Komorowski, M, Koentges G, Finkenstädt, B and Rand, DA, (2013), A hierarchical model of transcriptional dynamics allows robust estimation of transcription rates in populations of single cells with variable gene copy number, Bioinformatics 2013, 29 (12): 1519-1525. doi: 10.1093/bioinformatics/btt201.
Dafyd J. Jenkins; Barbel Finkenstädt; David A. Rand (2013), A temporal switch model for estimating transcriptional activity in gene expression. Bioinformatics 2013 May 1; 29(9): 1158–1165. doi:10.1093/bioinformatics/btt111 (link)
Peter D Gould, Nicolas Ugarte, Mirela Domijan, Maria Costa, Julia Foreman, Dana MacGregor, Ken Rose, Jayne Griffiths, Andrew J Millar, Bärbel Finkenstädt, Steven Penfield, David A Rand, Karen J Halliday & Anthony J W Hall (2013), Network balance via CRY signalling controls the Arabidopsis circadian clock over ambient temperatures, Molecular Systems Biology 2013 9:650; doi:10.1038/msb.2013.7; (link)
Windram O, Madhou P, McHattie S, Hickman R, Cooke E, Jenkins DJ, Penfold CA, Baxter L, Breeze E, Kiddle SJ, Rhodes J, Atwell S, Kliebenstein DJ, Kim Y-S, Stegle O, Borgwardt K, Zhang C, Tabrett A, Legaie R, Moore J, Finkenstädt B, Wild DL, Mead A, Rand DA, Beynon J, Ott S, Buchanan-Wollaston V, Denby KJ (2012) Arabidopsis defence against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis, Plant Cell 2012 24 (10), 3949 - 3965; (link)
Ferreira, M., Finkenstädt , B., Oliveira, B.M.P.M., Pinto, Alberto A. and A.N. Yannacopoulos, (2012), On the convergence to Walrasian prices in random matching Edgeworthian economies, Central European Journal of Operations Research (CJOR) 2012, 20 (3), pp 485-495 (link)
Harper CV, Finkenstädt B, Woodcock DJ, Friedrichsen S, Semprini S, et al. (2011) Dynamic Analysis of Stochastic Transcription Cycles. PLoS Biology 2011 9(4): e1000607. doi:10.1371/journal.pbio.1000607 (link)
Rittman M, Hoffmann SV, Gilroy E, Hicks MR, Finkenstädt B, Rodger A (2011) Probing the structure of long DNA molecules in solution using synchrotron radiation linear dichroism. Physical Chemistry Chemical Physics (PCCP) 2011, 14, 353-366 DOI: 10.1039/C1CP22371B; (link)
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 2011, 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 2010, 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; (link)
Heron, E., Finkenstädt, B. F. and Rand, D.A., (2007), Bayesian Inference for dynamic transcriptional regulation; the Hes1 system as a case study. Bioinformatics 2007, 23 (19), 2589-2595; (link)
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.