Hoksza D, Gawron P, Ostaszewski M, Hasenauer J, Schneider R.
Closing the gap between formats for storing layout information in systems biology.
Briefings in Bioinformatics, 2020, ISSN 1467-5463. doi: 10.1093/bib/bbaa030. [ABSTRACT]

Schmiester L, Schälte Y, Fröhlich F, Hasenauer J, Weindl D.
Efficient parameterization of large-scale dynamic models based on relative measurements.
Bioinformatics. 2020 Jan 15;36(2):594-602. doi: 10.1093/bioinformatics/btz581. [ABSTRACT]

Schmiester L, Weindl D, Hasenauer J.
Parameterization of mechanistic models from qualitative data using an efficient optimal scaling approach.
J Math Biol. 2020 Aug;81(2):603-623. doi: 10.1007/s00285-020-01522-w. [ABSTRACT]


Li H, Shukla S, Frappart L, Herrlich P, Ploubidou A.
cd44 deletion suppresses atypia in the precancerous mouse testis.
Mol Carcinog. 2019 May;58(5):621-626. doi: 10.1002/mc.22961. [ABSTRACT]

Villaverde AF.
Observability and Structural Identifiability of Nonlinear Biological Systems.
Complexity. 2019 Jan; doi: 10.1155/2019/8497093. [ABSTRACT]

Villaverde AF, Evans ND, Chappell MJ, Banga JR.
Input-Dependent Structural Identifiabiltiy of Nonlinear Systems.
IEEE Control Systems Letters 2019, 3(2):272-277; doi:110.1109/lcsys.2018.2868608. [ABSTRACT]

Villaverde AF, Tsiantis N, Banga JR.
Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models. 
J R Soc Interface. 2019 Jul 26;16(156):20190043. doi: 10.1098/rsif.2019.0043. [ABSTRACT]

Villaverde AF, Raimúndez E, Hasenauer J, Banga JR.
A Comparison of Methods for Quantifying Prediction Uncertainty in Systems Biology.  
IFAC-PapersOnLine. 2019;52(56):45-51. doi: 10.1016/j.ifacol.2019.12.234 [ABSTRACT]

Kapfer E-M, Stapor P, Hasenauer J.
Challenges in the Calibration of Large-Scale Ordinary Differential Equation Models.
IFAC-PapersOnLine. 2019;52(56):58-64. doi: 10.1016/j.ifacol.2019.12.236 [ABSTRACT]

Terje Lines G, Paszkowski L, Schmiester L, Weindl D, Stapor P, Hasenauer J.
Efficient Computation of Steady States in Large-Scale ODE Models of Biochemical Reaction Networks.
IFAC-PapersOnLine. 2019;52(56):32-37. doi: 10.1016/j.ifacol.2019.12.232 [ABSTRACT]

Villaverde AF, Banga JR.
Análisis de observabilidad e identificabilidad estructural de modelos no lineales: aplicación a la vía de señalización JAK/STAT.
Libra Acta. 2019:631-638. doi: 10.17979/spudc.9788497497169.631. [ABSTRACT]


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.
Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model.
Cell Syst. 2018 Dec 26; 7(6):567-579; doi: 10.1016/j.cels.2018.10.013.  [ABSTRACT]

Villaverde AF, Fröhlich F, Weindl D, Hasenauer J, Banga JR.
Benchmarking optimization methods for parameter estimation in large kinetic models.
Bioinformatics. 2018 Aug 24;bty736. doi.org/10.1093/bioinformatics/bty736. [ABSTRACT]

Ballnus B, Schaper S, Theis FJ, Hasenauer J.
Bayesian parameter estimation for biochemical reaction networks using region-based adaptive parallel tempering.
Bioinformatics. 2018 Jul 1;34(13):i494-i501. doi: 10.1093/bioinformatics/bty229. [ABSTRACT]

Ligon TS, Fröhlich F, Chis OT, Banga JR, Balsa-Canto E, Hasenauer J.
GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.
Bioinformatics. 2018 Apr 15;34(8):1421-1423. doi: 10.1093/bioinformatics/btx735. [ABSTRACT]

Stapor P, Weindl D, Ballnus B, Hug S, Loos C, Fiedler A, Krause S, Hroß S, Fröhlich F, Hasenauer J, Wren J.
PESTO: Parameter EStimation TOolbox
Bioinformatics. 2018 Feb 15;34(4):705-707. doi: 10.1093/bioinformatics/btx676. [ABSTRACT]

Yannick S, Stapor P, Hasenauer J.
Evaluation of Derivative-Free Optimizers for Parameter Estimation in Systems Biology
IFAC-PapersOnLine, Issue 51/19, 2018, 98-101. doi:10.1016/j.ifacol.2018.09.025 [ABSTRACT]

Villaverde AF, Evans ND, Chappell MJ, Banga JR.
Sufficiently Exciting Inputs for Structurally Identifiable Systems Biology Models
IFAC-PapersOnLine, Issue 51/19, 2018, 16-19. doi:10.1016/j.ifacol.2018.09.015 [ABSTRACT]

Stapor P, Fröhlich F, Hasenauer J.
Optimization and profile calculation of ODE models using second-order adjoint sensitivity analysis
Bioinformatics. 2018 Jul 1;34(13):i151-i159. doi: 10.1093/bioinformatics/bty230. [ABSTRACT]

Loos C, Krause S, Hasenauer J.
Hierarchical optimization for the efficient parametrization of ODE models.
Bioinformatics. 2018 Dec 15;34(24):4266-4273. doi: 10.1093/bioinformatics/bty514. [ABSTRACT]

Feigelman J, Weindl D, Marr C, Hasenauer J.
LNA++: Linear Noise Approximation with First and Second-Order Sensitivities.
Issue Proceedings of the 16th International Conference on Computational Methods in Systems Biology, 2018: 300-306. doi: 10.5281/zenodo.1287771. [ABSTRACT]


Bruderer R, Bernhardt OM, Gandhi T, Xuan Y, Sondermann J, Schmidt M, Gomez-Varela D, Reiter L.
Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results.
Mol Cell Proteomics 2017 Dec;16(12):2296-2309. doi: 10.1074/mcp.RA117.000314. Epub 2017 Oct 25. [ABSTRACT]

Ogilvie LA, Kovachev A, Wierling C., Lange BMH and Lehrach H.
Models of Models: A Translational Route for Cancer Treatment and Drug Development
Front. Oncol., 19 September 2017. doi: 10.3389/fonc.2017.00219. [ABSTRACT]

Villaverde AF, Becker K, Banga JR.
PREMER: a Tool to Infer Biological Networks
IEEE/ACM Trans Comput Biol Bioinform. 2017 Oct 4. doi: 10.1109/TCBB.2017.2758786. [ABSTRACT]

Gábor A, Villaverde AF, Banga JR.
Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems
BMC Syst Biol. 2017 May 5;11(1):54. doi: 10.1186/s12918-017-0428-y. [ABSTRACT]

Villaverde AF, Banga JR.
Structural Properties of Dynamic Systems Biology Models: Identifiability, Reachability and Initial Conditions.
Processes. 2017;5(1):5(4):29. doi: 10.3390/pr5020029. [ABSTRACT]


Villaverde AF, Barreiro A, Papachristodoulou A.
Structural Identifiability of Dynamic Systems Biology Models
PLoS Computational Biology 2016;12(10):e1005153 doi: 10.1371/journal.pcbi.1005153. [ABSTRACT]

Chis OT, Villaverde AF, Banga JR, Balsa-Canto E.
On the relationship between sloppiness and identifiability
Mathematical Biosciences 2016;282:147-161. doi: 10.1016/j.mbs.2016.10.009. Epub 2016 Oct 24 [ABSTRACT]

Villaverde AF, Becker K, Banga JR.
PREMER: Parallel Reverse Engineering of Biological Networks with Information Theory. In: Bartocci E., Lio P., Paoletti N. (eds)
Computational Methods in Systems Biology
CMSB 2016. Lecture Notes in Computer Science, vol 9859. Springer, Cham. [ABSTRACT]

Villaverde AF, Barreiro A, Papachristodoulou A.
Structural Identifiability Analysis via Extended Observability and Decomposition
IFAC-Papers On Line 2016;49(26): 171-177. doi: 10.1016/j.ifacol.2016.12.121. [ABSTRACT]