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Items: 1 to 50 of 57

1.

Inference of finite mixture models and the effect of binning.

Geissen EM, Hasenauer J, Radde NE.

Stat Appl Genet Mol Biol. 2019 Jul 26;18(4). pii: /j/sagmb.2019.18.issue-4/sagmb-2018-0035/sagmb-2018-0035.xml. doi: 10.1515/sagmb-2018-0035.

PMID:
31348764
2.

Efficient parameterization of large-scale dynamic models based on relative measurements.

Schmiester L, Schälte Y, Fröhlich F, Hasenauer J, Weindl D.

Bioinformatics. 2019 Jul 26. pii: btz581. doi: 10.1093/bioinformatics/btz581. [Epub ahead of print]

PMID:
31347657
3.

Continuous analogue to iterative optimization for PDE-constrained inverse problems.

Boiger R, Fiedler A, Hasenauer J, Kaltenbacher B.

Inverse Probl Sci Eng. 2018 Jul 10;27(6):710-734. doi: 10.1080/17415977.2018.1494167. eCollection 2019.

4.

Mechanistic description of spatial processes using integrative modelling of noise-corrupted imaging data.

Hross S, Theis FJ, Sixt M, Hasenauer J.

J R Soc Interface. 2018 Dec 21;15(149):20180600. doi: 10.1098/rsif.2018.0600.

5.

Inferring population dynamics from single-cell RNA-sequencing time series data.

Fischer DS, Fiedler AK, Kernfeld EM, Genga RMJ, Bastidas-Ponce A, Bakhti M, Lickert H, Hasenauer J, Maehr R, Theis FJ.

Nat Biotechnol. 2019 Apr;37(4):461-468. doi: 10.1038/s41587-019-0088-0. Epub 2019 Apr 1.

PMID:
30936567
6.

Erratum: Publisher Correction: Multi-experiment nonlinear mixed effect modeling of single-cell translation kinetics after transfection.

Fröhlich F, Reiser A, Fink L, Woschée D, Ligon T, Theis FJ, Rädler JO, Hasenauer J.

NPJ Syst Biol Appl. 2019 Mar 7;5:11. doi: 10.1038/s41540-019-0083-6. eCollection 2019.

7.

Benchmarking optimization methods for parameter estimation in large kinetic models.

Villaverde AF, Fröhlich F, Weindl D, Hasenauer J, Banga JR.

Bioinformatics. 2019 Mar 1;35(5):830-838. doi: 10.1093/bioinformatics/bty736.

8.

Comparison of null models for combination drug therapy reveals Hand model as biochemically most plausible.

Sinzger M, Vanhoefer J, Loos C, Hasenauer J.

Sci Rep. 2019 Feb 28;9(1):3002. doi: 10.1038/s41598-019-38907-x.

9.

Benchmark problems for dynamic modeling of intracellular processes.

Hass H, Loos C, Raimúndez-Álvarez E, Timmer J, Hasenauer J, Kreutz C.

Bioinformatics. 2019 Sep 1;35(17):3073-3082. doi: 10.1093/bioinformatics/btz020.

10.

Increasing Neural Stem Cell Division Asymmetry and Quiescence Are Predicted to Contribute to the Age-Related Decline in Neurogenesis.

Bast L, Calzolari F, Strasser MK, Hasenauer J, Theis FJ, Ninkovic J, Marr C.

Cell Rep. 2018 Dec 18;25(12):3231-3240.e8. doi: 10.1016/j.celrep.2018.11.088.

11.

Multi-experiment nonlinear mixed effect modeling of single-cell translation kinetics after transfection.

Fröhlich F, Reiser A, Fink L, Woschée D, Ligon T, Theis FJ, Rädler JO, Hasenauer J.

NPJ Syst Biol Appl. 2018 Dec 10;5:1. doi: 10.1038/s41540-018-0079-7. eCollection 2019. Erratum in: NPJ Syst Biol Appl. 2019 Mar 7;5:11.

12.

Scalable Inference of Ordinary Differential Equation Models of Biochemical Processes.

Fröhlich F, Loos C, Hasenauer J.

Methods Mol Biol. 2019;1883:385-422. doi: 10.1007/978-1-4939-8882-2_16. Review.

PMID:
30547409
13.

Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model.

Fröhlich F, Kessler T, Weindl D, Shadrin A, Schmiester L, Hache H, Muradyan A, Schütte M, Lim JH, Heinig M, Theis FJ, Lehrach H, Wierling C, Lange B, Hasenauer J.

Cell Syst. 2018 Dec 26;7(6):567-579.e6. doi: 10.1016/j.cels.2018.10.013. Epub 2018 Nov 28.

14.

Hierarchical optimization for the efficient parametrization of ODE models.

Loos C, Krause S, Hasenauer J.

Bioinformatics. 2018 Dec 15;34(24):4266-4273. doi: 10.1093/bioinformatics/bty514.

15.

Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis.

Stapor P, Fröhlich F, Hasenauer J.

Bioinformatics. 2018 Jul 1;34(13):i151-i159. doi: 10.1093/bioinformatics/bty230.

16.

Bayesian parameter estimation for biochemical reaction networks using region-based adaptive parallel tempering.

Ballnus B, Schaper S, Theis FJ, Hasenauer J.

Bioinformatics. 2018 Jul 1;34(13):i494-i501. doi: 10.1093/bioinformatics/bty229.

17.

pyABC: distributed, likelihood-free inference.

Klinger E, Rickert D, Hasenauer J.

Bioinformatics. 2018 Oct 15;34(20):3591-3593. doi: 10.1093/bioinformatics/bty361.

PMID:
29762723
18.

A Hierarchical, Data-Driven Approach to Modeling Single-Cell Populations Predicts Latent Causes of Cell-To-Cell Variability.

Loos C, Moeller K, Fröhlich F, Hucho T, Hasenauer J.

Cell Syst. 2018 May 23;6(5):593-603.e13. doi: 10.1016/j.cels.2018.04.008. Epub 2018 May 2.

19.

Community-driven roadmap for integrated disease maps.

Ostaszewski M, Gebel S, Kuperstein I, Mazein A, Zinovyev A, Dogrusoz U, Hasenauer J, Fleming RMT, Le Novère N, Gawron P, Ligon T, Niarakis A, Nickerson D, Weindl D, Balling R, Barillot E, Auffray C, Schneider R.

Brief Bioinform. 2019 Mar 25;20(2):659-670. doi: 10.1093/bib/bby024.

20.

PKA-RII subunit phosphorylation precedes activation by cAMP and regulates activity termination.

Isensee J, Kaufholz M, Knape MJ, Hasenauer J, Hammerich H, Gonczarowska-Jorge H, Zahedi RP, Schwede F, Herberg FW, Hucho T.

J Cell Biol. 2018 Jun 4;217(6):2167-2184. doi: 10.1083/jcb.201708053. Epub 2018 Apr 3.

21.

Whither systems medicine?

Apweiler R, Beissbarth T, Berthold MR, Blüthgen N, Burmeister Y, Dammann O, Deutsch A, Feuerhake F, Franke A, Hasenauer J, Hoffmann S, Höfer T, Jansen PL, Kaderali L, Klingmüller U, Koch I, Kohlbacher O, Kuepfer L, Lammert F, Maier D, Pfeifer N, Radde N, Rehm M, Roeder I, Saez-Rodriguez J, Sax U, Schmeck B, Schuppert A, Seilheimer B, Theis FJ, Vera J, Wolkenhauer O.

Exp Mol Med. 2018 Mar 2;50(3):e453. doi: 10.1038/emm.2017.290. Review.

22.

Effects of trastuzumab and afatinib on kinase activity in gastric cancer cell lines.

Keller S, Zwingenberger G, Ebert K, Hasenauer J, Wasmuth J, Maier D, Haffner I, Schierle K, Weirich G, Luber B.

Mol Oncol. 2018 Apr;12(4):441-462. doi: 10.1002/1878-0261.12170. Epub 2018 Mar 10.

23.

Evaluation of epidermal growth factor receptor signaling effects in gastric cancer cell lines by detailed motility-focused phenotypic characterization linked with molecular analysis.

Keller S, Kneissl J, Grabher-Meier V, Heindl S, Hasenauer J, Maier D, Mattes J, Winter P, Luber B.

BMC Cancer. 2017 Dec 13;17(1):845. doi: 10.1186/s12885-017-3822-3.

24.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

Ligon TS, Fröhlich F, Chis OT, Banga JR, Balsa-Canto E, Hasenauer J.

Bioinformatics. 2018 Apr 15;34(8):1421-1423. doi: 10.1093/bioinformatics/btx735.

25.

PESTO: Parameter EStimation TOolbox.

Stapor P, Weindl D, Ballnus B, Hug S, Loos C, Fiedler A, Krause S, Hroß S, Fröhlich F, Hasenauer J, Wren J.

Bioinformatics. 2018 Feb 15;34(4):705-707. doi: 10.1093/bioinformatics/btx676.

26.

A scalable moment-closure approximation for large-scale biochemical reaction networks.

Kazeroonian A, Theis FJ, Hasenauer J.

Bioinformatics. 2017 Jul 15;33(14):i293-i300. doi: 10.1093/bioinformatics/btx249.

27.

Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems.

Ballnus B, Hug S, Hatz K, Görlitz L, Hasenauer J, Theis FJ.

BMC Syst Biol. 2017 Jun 24;11(1):63. doi: 10.1186/s12918-017-0433-1.

28.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks.

Fröhlich F, Kaltenbacher B, Theis FJ, Hasenauer J.

PLoS Comput Biol. 2017 Jan 23;13(1):e1005331. doi: 10.1371/journal.pcbi.1005331. eCollection 2017 Jan.

29.

Parallelization and High-Performance Computing Enables Automated Statistical Inference of Multi-scale Models.

Jagiella N, Rickert D, Theis FJ, Hasenauer J.

Cell Syst. 2017 Feb 22;4(2):194-206.e9. doi: 10.1016/j.cels.2016.12.002. Epub 2017 Jan 11.

30.

Robust parameter estimation for dynamical systems from outlier-corrupted data.

Maier C, Loos C, Hasenauer J.

Bioinformatics. 2017 Mar 1;33(5):718-725. doi: 10.1093/bioinformatics/btw703.

PMID:
28062444
31.

Parameter estimation for dynamical systems with discrete events and logical operations.

Fröhlich F, Theis FJ, Rädler JO, Hasenauer J.

Bioinformatics. 2017 Apr 1;33(7):1049-1056. doi: 10.1093/bioinformatics/btw764.

PMID:
28040696
32.

Characterization of Rare, Dormant, and Therapy-Resistant Cells in Acute Lymphoblastic Leukemia.

Ebinger S, Özdemir EZ, Ziegenhain C, Tiedt S, Castro Alves C, Grunert M, Dworzak M, Lutz C, Turati VA, Enver T, Horny HP, Sotlar K, Parekh S, Spiekermann K, Hiddemann W, Schepers A, Polzer B, Kirsch S, Hoffmann M, Knapp B, Hasenauer J, Pfeifer H, Panzer-Grümayer R, Enard W, Gires O, Jeremias I.

Cancer Cell. 2016 Dec 12;30(6):849-862. doi: 10.1016/j.ccell.2016.11.002. Epub 2016 Dec 1.

33.

Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints.

Fiedler A, Raeth S, Theis FJ, Hausser A, Hasenauer J.

BMC Syst Biol. 2016 Aug 22;10(1):80. doi: 10.1186/s12918-016-0319-7.

34.

Inference for Stochastic Chemical Kinetics Using Moment Equations and System Size Expansion.

Fröhlich F, Thomas P, Kazeroonian A, Theis FJ, Grima R, Hasenauer J.

PLoS Comput Biol. 2016 Jul 22;12(7):e1005030. doi: 10.1371/journal.pcbi.1005030. eCollection 2016 Jul.

35.

MEMO: multi-experiment mixture model analysis of censored data.

Geissen EM, Hasenauer J, Heinrich S, Hauf S, Theis FJ, Radde NE.

Bioinformatics. 2016 Aug 15;32(16):2464-72. doi: 10.1093/bioinformatics/btw190. Epub 2016 Apr 19.

36.

Analysis of CFSE time-series data using division-, age- and label-structured population models.

Hross S, Hasenauer J.

Bioinformatics. 2016 Aug 1;32(15):2321-9. doi: 10.1093/bioinformatics/btw131. Epub 2016 Mar 8.

PMID:
27153577
37.

Combinatorial Histone Acetylation Patterns Are Generated by Motif-Specific Reactions.

Blasi T, Feller C, Feigelman J, Hasenauer J, Imhof A, Theis FJ, Becker PB, Marr C.

Cell Syst. 2016 Jan 27;2(1):49-58. doi: 10.1016/j.cels.2016.01.002. Epub 2016 Jan 27.

38.

CERENA: ChEmical REaction Network Analyzer--A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics.

Kazeroonian A, Fröhlich F, Raue A, Theis FJ, Hasenauer J.

PLoS One. 2016 Jan 25;11(1):e0146732. doi: 10.1371/journal.pone.0146732. eCollection 2016.

39.

Network plasticity of pluripotency transcription factors in embryonic stem cells.

Filipczyk A, Marr C, Hastreiter S, Feigelman J, Schwarzfischer M, Hoppe PS, Loeffler D, Kokkaliaris KD, Endele M, Schauberger B, Hilsenbeck O, Skylaki S, Hasenauer J, Anastassiadis K, Theis FJ, Schroeder T.

Nat Cell Biol. 2015 Oct;17(10):1235-46. doi: 10.1038/ncb3237. Epub 2015 Sep 21.

PMID:
26389663
40.

Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.

Raue A, Steiert B, Schelker M, Kreutz C, Maiwald T, Hass H, Vanlier J, Tönsing C, Adlung L, Engesser R, Mader W, Heinemann T, Hasenauer J, Schilling M, Höfer T, Klipp E, Theis F, Klingmüller U, Schöberl B, Timmer J.

Bioinformatics. 2015 Nov 1;31(21):3558-60. doi: 10.1093/bioinformatics/btv405. Epub 2015 Jul 3.

PMID:
26142188
41.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

Hasenauer J, Hasenauer C, Hucho T, Theis FJ.

PLoS Comput Biol. 2014 Jul 3;10(7):e1003686. doi: 10.1371/journal.pcbi.1003686. eCollection 2014 Jul.

42.

Dominant negative effects of tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) receptor 4 on TRAIL receptor 1 signaling by formation of heteromeric complexes.

Neumann S, Hasenauer J, Pollak N, Scheurich P.

J Biol Chem. 2014 Jun 6;289(23):16576-87. doi: 10.1074/jbc.M114.559468. Epub 2014 Apr 24.

43.

iVUN: interactive Visualization of Uncertain biochemical reaction Networks.

Vehlow C, Hasenauer J, Kramer A, Raue A, Hug S, Timmer J, Radde N, Theis FJ, Weiskopf D.

BMC Bioinformatics. 2013;14 Suppl 19:S2. doi: 10.1186/1471-2105-14-S19-S2. Epub 2013 Nov 12.

44.

Modeling of 2D diffusion processes based on microscopy data: parameter estimation and practical identifiability analysis.

Hock S, Hasenauer J, Theis FJ.

BMC Bioinformatics. 2013;14 Suppl 10:S7. doi: 10.1186/1471-2105-14-S10-S7. Epub 2013 Aug 12.

45.

Pain modulators regulate the dynamics of PKA-RII phosphorylation in subgroups of sensory neurons.

Isensee J, Diskar M, Waldherr S, Buschow R, Hasenauer J, Prinz A, Allgöwer F, Herberg FW, Hucho T.

J Cell Sci. 2014 Jan 1;127(Pt 1):216-29. doi: 10.1242/jcs.136580. Epub 2013 Nov 4.

46.

Determinants of robustness in spindle assembly checkpoint signalling.

Heinrich S, Geissen EM, Kamenz J, Trautmann S, Widmer C, Drewe P, Knop M, Radde N, Hasenauer J, Hauf S.

Nat Cell Biol. 2013 Nov;15(11):1328-39. doi: 10.1038/ncb2864. Epub 2013 Oct 27.

PMID:
24161933
47.

Method of conditional moments (MCM) for the Chemical Master Equation: a unified framework for the method of moments and hybrid stochastic-deterministic models.

Hasenauer J, Wolf V, Kazeroonian A, Theis FJ.

J Math Biol. 2014 Sep;69(3):687-735. doi: 10.1007/s00285-013-0711-5. Epub 2013 Aug 6.

PMID:
23918091
48.

Wound-healing growth factor, basic FGF, induces Erk1/2-dependent mechanical hyperalgesia.

Andres C, Hasenauer J, Ahn HS, Joseph EK, Isensee J, Theis FJ, Allgöwer F, Levine JD, Dib-Hajj SD, Waxman SG, Hucho T.

Pain. 2013 Oct;154(10):2216-26. doi: 10.1016/j.pain.2013.07.005. Epub 2013 Jul 16.

PMID:
23867734
49.

Sharpening of expression domains induced by transcription and microRNA regulation within a spatio-temporal model of mid-hindbrain boundary formation.

Hock S, Ng YK, Hasenauer J, Wittmann D, Lutter D, Trümbach D, Wurst W, Prakash N, Theis FJ.

BMC Syst Biol. 2013 Jun 25;7:48. doi: 10.1186/1752-0509-7-48.

50.

High-dimensional Bayesian parameter estimation: case study for a model of JAK2/STAT5 signaling.

Hug S, Raue A, Hasenauer J, Bachmann J, Klingmüller U, Timmer J, Theis FJ.

Math Biosci. 2013 Dec;246(2):293-304. doi: 10.1016/j.mbs.2013.04.002. Epub 2013 Apr 16.

PMID:
23602931

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