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Beniamino Hadj-Amar, Bärbel Finkenstädt, Mark Fiecas, Robert Huckstepp, A spectral hidden Markov model for non stationary oscillatory processes, arXiv:2001.01676

Panayiota Touloupou, Bärbel Finkenstädt, Thomas E. Besser, Nigel P. French, and Simon E.F. Spencer, Bayesian inference for multi-strain epidemics with application to Escherichia coli O157:H7 in feedlot cattle, submitted to Annals of Applied Statistics.

Massimo Cavallaro, Mark Walsh, Matt Jones, James Teahan, Simone Tiberi, Bärbel Finkenstädt and Daniel Hebenstreit, 3’-5’ crosstalk contributes to transcriptional bursting. Preprint.

Komarzynski, S, Bolborea, M, Huang, Q, Finkenstädt, B, Lévi, F (2019), Predictability of individual circadian phase during daily routine for medical applications of circadian clocks , Journal of Clinical Investigation (JCI) Insight, 2019, link

Hadj-Amar, B., Finkenstädt, B., Fiecas, M., Lévi, F. & Huckstepp, R. (2019), Bayesian Model Search for Nonstationary Periodic Time Series , Journal of the American Statistical Association, 2019, link

Momiji, H, Hassall, K, Featherstone, K, McNamara, AV, Patist, AL, Spiller, DG, White, MRH, Davis, JRE, Finkenstädt, B, Rand, DA (2019), Juxtacrine signalling and space-time coordinated prolactin production, Plos Computational Biology, 2019, link

Calderazzo, S, Brancaccio, M and Finkenstädt, B (2019), Filtering and Inference for stochastic oscillators with distributed delays, Bioinformatics, 2019, 35 (8): 1380–1387 link.

Tiberi, S, Walsh, M, Cavallaro, M, Hebenstreit, D and Finkenstädt, B (2018), Bayesian inference on stochastic gene transcription from flow cytometry data, Bioinformatics, 2018, 34(17): i647–i655. link

Komarzynski S, Huang Q, Innominato PF, Maurice M, Arbaud A, Beau J, Bouchahda M, Ulusakarya A, Beaumatin N, Virasolvy F, Breda G, Finkenstädt B and Lévi F (2018), Real-time capture of inter- and intra-subject variations in human circadian coordination in healthy and cancerous persons at home, J Med Internet Res 2018 doi:10.2196/jmir.9779 

Huang, Q, Cohen, D, Komarzynski, S, Li, XM, Innominato, P, Lévi, F and Finkenstädt, B (2018), Hidden Markov Models for monitoring Circadian Rhythmicity in Telemetric Activity Data, Journal of the Royal Society - Interface 7 Feb 2018.

Huang, Q, Komarzynski, S, Innominato, P, Lévi, F and Finkenstädt, B, Quantifiers of Circadian Rhythmicity in Telemetric Activity Data, to appear in SAGE Journal Digital Health 2018.

Dunham, L, Momiji, H, Harper, C, Hey, K, McNamara, A, Featherstone, K, Spiller, D, Rand, D, Finkenstädt, B, White, M, Davis, J (2017), Asymmetrical switching behaviour in transcriptional control, Cell Systems 2017, Published Online: November 15, 2017.

Minas, G, Jenkins, D, Rand, DA and Finkenstädt B (2017), Inferring transcriptional logic from multiple dynamic experiments, Bioinformatics, 2017:1-8.

Minas, G, Momiji, H, Jenkins, D, Costa, MJ, Rand, DA and Finkenstädt B (2017), ReTrOS: A MAT- LAB Toolbox for Reconstructing Transcriptional Activity from Gene and Protein Expression Data, BMC Bioinformatics, 2017, 18:316 

Bechtold, U, Penfold, C, Jenkins, D, Legaie, R, Moore, J, Lawson, T, Matthews, J, Vialet- Chabrand, S, Baxter, L, Subramaniam, S, Hickman, R, Florance, H, Sambles, C, Salmon, D, Feil, R, Bowden, L, Hill, C, Baker, N, Lunn, J, Finkenstädt B, Mead, A, Buchanan-Wollaston, V, Beynon, J, Rand, D, Wild, D, Denby, K, Ott, S, Smirnoff, N, Mullineaux, P, Time-series transcriptomics reveals that AGAMOUS-LIKE22 links primary metabolism to developmental processes in drought-stressed Arabidopsis, The Plant Cell, Advance Publication February 3, 2016.

Featherstone, K, Hey, K, Momiji, H, McNamara, AV, Patist, AL, Woodburn, J, Spiller, DG, Christian, HC, McNeilly, AS, Mullins, JJ, Finkenstädt BF, Rand, DA, White, MRH, Davis, JRE, Spatially coordinated dynamic gene transcription in living pituitary tissue, eLife, 2015; 5:e08494.

Hey, K, Momiji, H, Featherstone K, Davis J, White M, Rand D, Finkenstädt B, A stochastic transcriptional switch model for single cell imaging data, Biostatistics, Advance Access March 2015.

Sidaway-Lee, K, Costa, MJ, Rand, DA, Finkenstädt B and Penfield, S, Direct measurement of transcription rates reveals multiple mechanisms for configuration of the Arabidopsisambient temperature response, Genome Biology, 2014, 15:R45

Finkenstädt B.F., Woodcock, D.J., Komorowski, M., Harper, C.V., Davis, J.R.E., White, M.R.H., Rand, D.A., Quantifying intrinsic and extrinsic noise in gene transcription: an application to single cell imaging data, Annals of Applied Statistics, 2013, 7(4):1960- 82.

Costa M.J., Finkenstädt B.F., Gould, P.D, Foreman, J., Halliday, K., Hall, A., Roche, V., L ́evi, F. and Rand, D., Inference on periodicity of circadian time series, Biostatistics, 2013, 14(4):792-806.

Woodcock, DJ, Vance KW, Komorowski, M, Koentges G, Finkenstädt B and Rand, DA, 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.

Jenkins, D., Finkenstädt B.F. and Rand, D., 2013, A temporal switch model for estimating transcriptional activity in gene expression, Bioinformatics, 2013, 29(9):1158-65.

Gould, PD, Ugarte,N , Domijan, M, Costa, MJ, Foreman,J, MacGregor,D, Rose, K, Griffiths, J., Millar, AJ, Finkenstädt, B, Penfield, S, Rand, DA, Halliday, K and Hall, A J W, Network balance via CRY signalling controls the Arabidopsis circadian clock over ambient temperatures, Molecular Systems Biology, 2013, 9:650.

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, Arabidopsis defence against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis, Plant Cell, 2012 , 24(10):3949 - 3965.

Ferreira, M., Finkenstädt , B., Oliveira, B.M.P.M., Pinto, Alberto A. and A.N. Yanna- copoulos, (2011), On the convergence to Walrasian prices in random matching Edgeworthian economies, Cent. Europ. J. of Op. Res., 2012, 20 (3), 485-495.

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, 2011, 14, 353-366

Ferreira, M., Finkenstädt , B., Oliveira, B.M.P.M., Pinto, A. 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 Berlin Heidelberg 2011.

Harper, C.V., Finkenstädt , B., Friedrichsen S., Woodcock D., Semprini S., Spiller D., Mullins J.J., Rand D.A., Davis J.R.E. and White M.R.H., Dynamic Analysis of Stochastic Transcription Cycles. PLoS Biology 9(4), 2011, e1000607.

Komorowski, M., Finkenstädt , B., Rand, D. A. , Using single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression, Biophysical Journal, 2010, 98(12): 2759-2769.

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.

Finkenstädt B., Heron, E., Komorowski, M., Edwards, K., Tang, S., Harper, C.V., Davis, J.R.E., White, M.R.H., Millar, A.J. and Rand, D.A., 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., Bayesian Inference for dynamic transcriptional regulation; the Hes1 system as a case study, Bioinformatics, 2007, 23(19): 2589-2595 (plus 13 pages of supplementary information)

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

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

Morton, A.M. and Finkenstädt B. F., Discrete-time modelling of disease incidence time series by using Markov Chain Monte Carlo methods, Journal of the Royal Statistical Society C (Applied Statistics), 2005, 54(3): 575-594.

Grenfell, B.T., Bjørnstad, O.N. and B.F. Finkenstädt, Dynamics of measles epidemics: Scal- ing noise, determinism and predictability with the TSIR model, Ecological Monographs, 2002, 72(2), 185-202.

Bjørnstad, O.N., Grenfell, B.T. and B.F. Finkenstädt Dynamics of measles epidemics: Estimating scaling of transmission rates using a time series SIR model, Ecological Monographs, 2002, 72(2), 185-202.

Finkenstädt B.F., Bjørnstad, O.N. and Grenfell, B.T., A stochastic model for extinction and recurrence of epidemics: Estimation and inference for measles outbreaks, Biostatistics, 2002, 3:493-510.

Finkenstädt B., Yao, Q. and Tong, H., A conditional density approach to the order de- termination of time series, Statistics and Computing, 2001, 11:229-240.

Yao, Q., Tong H., Finkenstädt B. and Stenseth N.C., Common structure in panels of short time series, Proceedings of the Royal Society B, 2000, 267:2457-2467.

Grenfell, B.T., Finkenstädt, B., Wilson, K., Coulson T.N. and Crawley, M.J., Nonlinearity and the Moran effect, Nature Communications, 2000, 406:847.

Finkenstädt, B. and Grenfell, B., Time series modelling of childhood diseases: a dynamical systems approach, Journal of the Royal Statistical Society series C, 2000, 49:187-205.

Grenfell, B. and Finkenstädt B., Seasonality, stochasticity and population cycles, Res. Popul. Ecol., 1998, 40 (1): 141-143.

Rohani, P., Earn, D.J.D., Finkenstädt B. and Grenfell, B., Population dynamic interference among childhood diseases, Proceedings of the Royal Society B, 1998, 265:2033-2041.

Grenfell, B., Wilson, K., Finkenstädt B., Coulson, T.N., Murray, S., Albon, S.D., Pemberton, J.M., Clutton-Brock, T.H., Crawley, M.J., Noise and determinism in synchronized sheep dynamics, Nature, 1998, 394:674-77.

Finkenstädt B., Keeling M. and Grenfell, B., Patterns of density dependence in measles dynamics, Proceedings of the Royal Society B, 1998, 265:753-762.

Finkenstädt B. and Grenfell, B., Empirical determinants of measles metapopulation dynam- ics in England and Wales, Proceedings of the Royal Society B, 1998, 265: 211-220.

Finkenstädt B. and Kuhbier, P., Forecasting nonlinear economic time series: A simple test to accompany the nearest neighbour approach, Empirical Economics, 1995, 20:243-263.

Finkenstädt B. and Kuhbier, P., Principal components and overall sphericity: An application to chaotic time series, in: Dynamic economic models and optimal control, 1992, ed. G. Feichtinger, North Holland , 431-449.

Finkenstädt B. and Kuhbier, P., Chaotic dynamics in agricultural markets, Annals of Operation Research,1992, 37:73-96.

Stam, A., DeLorme, C., and Finkenstädt B., Cross national money-income causality for the floating exchange rate period: Has the influence of U.S. and German money persisted?, Journal of Macroeconomics, 1991, 13:207-237.

Research monographs and edited volumes

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

Finkenstädt B. and Rootzén, H. (eds), 2003, Extreme Values in Finance, Telecommunications, and the Environment, Monographs on Statistics and Applied Probability, CRC Press/Chapman and Hall.

Finkenstädt B. (1995) Nonlinear Dynamics in Economics: A theoretical and statistical approach to agricultural markets, Springer Lecture Notes in Economics and Mathematical Systems No. 426.