Format
Sort by
Items per page

Send to

Choose Destination

Best matches for Finkenstädt B[au]:

Search results

Items: 31

1.

Predictability of individual circadian phase during daily routine for medical applications of circadian clocks.

Komarzynski S, Bolborea M, Huang Q, Finkenstädt B, Lévi F.

JCI Insight. 2019 Sep 19;4(18). pii: 130423. doi: 10.1172/jci.insight.130423.

2.

Disentangling juxtacrine from paracrine signalling in dynamic tissue.

Momiji H, Hassall KL, Featherstone K, McNamara AV, Patist AL, Spiller DG, Christian HC, White MRH, Davis JRE, Finkenstädt BF, Rand DA.

PLoS Comput Biol. 2019 Jun 13;15(6):e1007030. doi: 10.1371/journal.pcbi.1007030. eCollection 2019 Jun.

3.

Bayesian inference on stochastic gene transcription from flow cytometry data.

Tiberi S, Walsh M, Cavallaro M, Hebenstreit D, Finkenstädt B.

Bioinformatics. 2018 Sep 1;34(17):i647-i655. doi: 10.1093/bioinformatics/bty568.

4.

Filtering and inference for stochastic oscillators with distributed delays.

Calderazzo S, Brancaccio M, Finkenstädt B.

Bioinformatics. 2019 Apr 15;35(8):1380-1387. doi: 10.1093/bioinformatics/bty782.

5.

Relevance of a Mobile Internet Platform for Capturing Inter- and Intrasubject Variabilities in Circadian Coordination During Daily Routine: Pilot Study.

Komarzynski S, Huang Q, Innominato PF, Maurice M, Arbaud A, Beau J, Bouchahda M, Ulusakarya A, Beaumatin N, Breda G, Finkenstädt B, Lévi F.

J Med Internet Res. 2018 Jun 11;20(6):e204. doi: 10.2196/jmir.9779.

6.

Hidden Markov models for monitoring circadian rhythmicity in telemetric activity data.

Huang Q, Cohen D, Komarzynski S, Li XM, Innominato P, Lévi F, Finkenstädt B.

J R Soc Interface. 2018 Feb;15(139). pii: 20170885. doi: 10.1098/rsif.2017.0885.

7.

Asymmetry between Activation and Deactivation during a Transcriptional Pulse.

Dunham LSS, Momiji H, Harper CV, Downton PJ, Hey K, McNamara A, Featherstone K, Spiller DG, Rand DA, Finkenstädt B, White MRH, Davis JRE.

Cell Syst. 2017 Dec 27;5(6):646-653.e5. doi: 10.1016/j.cels.2017.10.013. Epub 2017 Nov 15.

8.

Inferring transcriptional logic from multiple dynamic experiments.

Minas G, Jenkins DJ, Rand DA, Finkenstädt B.

Bioinformatics. 2017 Nov 1;33(21):3437-3444. doi: 10.1093/bioinformatics/btx407.

9.

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

Minas G, Momiji H, Jenkins DJ, Costa MJ, Rand DA, Finkenstädt B.

BMC Bioinformatics. 2017 Jun 26;18(1):316. doi: 10.1186/s12859-017-1695-8.

10.

Time-Series Transcriptomics Reveals That AGAMOUS-LIKE22 Affects Primary Metabolism and Developmental Processes in Drought-Stressed Arabidopsis.

Bechtold U, Penfold CA, Jenkins DJ, Legaie R, Moore JD, Lawson T, Matthews JS, Vialet-Chabrand SR, Baxter L, Subramaniam S, Hickman R, Florance H, Sambles C, Salmon DL, Feil R, Bowden L, Hill C, Baker NR, Lunn JE, Finkenstädt B, Mead A, Buchanan-Wollaston V, Beynon J, Rand DA, Wild DL, Denby KJ, Ott S, Smirnoff N, Mullineaux PM.

Plant Cell. 2016 Feb;28(2):345-66. doi: 10.1105/tpc.15.00910. Epub 2016 Feb 3.

11.

Spatially coordinated dynamic gene transcription in living pituitary tissue.

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 MR, Davis JR.

Elife. 2016 Feb 1;5:e08494. doi: 10.7554/eLife.08494.

12.

A stochastic transcriptional switch model for single cell imaging data.

Hey KL, Momiji H, Featherstone K, Davis JR, White MR, Rand DA, Finkenstädt B.

Biostatistics. 2015 Oct;16(4):655-69. doi: 10.1093/biostatistics/kxv010. Epub 2015 Mar 26.

13.

Direct measurement of transcription rates reveals multiple mechanisms for configuration of the Arabidopsis ambient temperature response.

Sidaway-Lee K, Costa MJ, Rand DA, Finkenstadt B, Penfield S.

Genome Biol. 2014 Mar 3;15(3):R45. doi: 10.1186/gb-2014-15-3-r45.

14.

Inference on periodicity of circadian time series.

Costa MJ, Finkenstädt B, Roche V, Lévi F, Gould PD, Foreman J, Halliday K, Hall A, Rand DA.

Biostatistics. 2013 Sep;14(4):792-806. doi: 10.1093/biostatistics/kxt020. Epub 2013 Jun 6.

15.

A hierarchical model of transcriptional dynamics allows robust estimation of transcription rates in populations of single cells with variable gene copy number.

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

Bioinformatics. 2013 Jun 15;29(12):1519-25. doi: 10.1093/bioinformatics/btt201. Epub 2013 May 14.

16.

Network balance via CRY signalling controls the Arabidopsis circadian clock over ambient temperatures.

Gould PD, Ugarte N, Domijan M, Costa M, Foreman J, Macgregor D, Rose K, Griffiths J, Millar AJ, Finkenstädt B, Penfield S, Rand DA, Halliday KJ, Hall AJ.

Mol Syst Biol. 2013;9:650. doi: 10.1038/msb.2013.7.

17.

A temporal switch model for estimating transcriptional activity in gene expression.

Jenkins DJ, Finkenstädt B, Rand DA.

Bioinformatics. 2013 May 1;29(9):1158-65. doi: 10.1093/bioinformatics/btt111. Epub 2013 Mar 11.

18.

Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis.

Windram O, Madhou P, McHattie S, Hill C, Hickman R, Cooke E, Jenkins DJ, Penfold CA, Baxter L, Breeze E, Kiddle SJ, Rhodes J, Atwell S, Kliebenstein DJ, Kim YS, Stegle O, Borgwardt K, Zhang C, Tabrett A, Legaie R, Moore J, Finkenstadt B, Wild DL, Mead A, Rand D, Beynon J, Ott S, Buchanan-Wollaston V, Denby KJ.

Plant Cell. 2012 Sep;24(9):3530-57. doi: 10.1105/tpc.112.102046. Epub 2012 Sep 28.

19.

Probing the structure of long DNA molecules in solution using synchrotron radiation linear dichroism.

Rittman M, Hoffmann SV, Gilroy E, Hicks MR, Finkenstadt B, Rodger A.

Phys Chem Chem Phys. 2012 Jan 7;14(1):353-66. doi: 10.1039/c1cp22371b. Epub 2011 Nov 16.

PMID:
22089140
20.

Dynamic analysis of stochastic transcription cycles.

Harper CV, Finkenstädt B, Woodcock DJ, Friedrichsen S, Semprini S, Ashall L, Spiller DG, Mullins JJ, Rand DA, Davis JR, White MR.

PLoS Biol. 2011 Apr;9(4):e1000607. doi: 10.1371/journal.pbio.1000607. Epub 2011 Apr 12.

21.

Using a single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression.

Komorowski M, Finkenstädt B, Rand D.

Biophys J. 2010 Jun 16;98(12):2759-69. doi: 10.1016/j.bpj.2010.03.032.

22.

Bayesian inference of biochemical kinetic parameters using the linear noise approximation.

Komorowski M, Finkenstädt B, Harper CV, Rand DA.

BMC Bioinformatics. 2009 Oct 19;10:343. doi: 10.1186/1471-2105-10-343.

23.

Reconstruction of transcriptional dynamics from gene reporter data using differential equations.

Finkenstädt B, Heron EA, Komorowski M, Edwards K, Tang S, Harper CV, Davis JR, White MR, Millar AJ, Rand DA.

Bioinformatics. 2008 Dec 15;24(24):2901-7. doi: 10.1093/bioinformatics/btn562. Epub 2008 Oct 30.

24.

Bayesian inference for dynamic transcriptional regulation; the Hes1 system as a case study.

Heron EA, Finkenstädt B, Rand DA.

Bioinformatics. 2007 Oct 1;23(19):2596-603. Epub 2007 Jul 28.

PMID:
17660527
25.
26.

Modelling antigenic drift in weekly flu incidence.

Finkenstädt BF, Morton A, Rand DA.

Stat Med. 2005 Nov 30;24(22):3447-61.

PMID:
16217845
27.

A stochastic model for extinction and recurrence of epidemics: estimation and inference for measles outbreaks.

Finkenstädt BF, Bjørnstad ON, Grenfell BT.

Biostatistics. 2002 Dec;3(4):493-510.

PMID:
12933594
28.

Common structure in panels of short ecological time-series.

Yao Q, Tong H, Finkenstädt B, Stenseth NC.

Proc Biol Sci. 2000 Dec 7;267(1460):2459-67.

29.

Population dynamic interference among childhood diseases.

Rohani P, Earn DJ, Finkenstädt B, Grenfell BT.

Proc Biol Sci. 1998 Nov 7;265(1410):2033-41.

30.

Patterns of density dependence in measles dynamics.

Finkenstädt B, Keeling M, Grenfell B.

Proc Biol Sci. 1998 May 7;265(1398):753-62.

31.

Empirical determinants of measles metapopulation dynamics in England and Wales.

Finkenstädt B, Grenfell B.

Proc Biol Sci. 1998 Feb 7;265(1392):211-20.

Supplemental Content

Loading ...
Support Center