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41.
Villaverde, A.F.* ; Fröhlich, F. ; Weindl, D. ; Hasenauer, J. & Banga, J.R.*: Benchmarking optimization methods for parameter estimation in large kinetic models. Bioinformatics 35, 830-838 (2019)
42.
Ballnus, B. ; Schaper, S.* ; Theis, F.J. & Hasenauer, J.: Bayesian parameter estimation for biochemical reaction networks using region-based adaptive parallel tempering. Bioinformatics 34, 494-501 (2018)
43.
Klinger, E. ; Rickert, D. & Hasenauer, J.: pyABC: Distributed, likelihood-free inference. Bioinformatics 34, 3591-3593 (2018)
44.
Loos, C. ; Krause, S. & Hasenauer, J.: Hierarchical optimization for the efficient parametrization of ODE models. Bioinformatics 34, 4266-4273 (2018)
45.
Stapor, P. et al.: PESTO: Parameter EStimation TOolbox. Bioinformatics 34, 705-707 (2018)
46.
Stapor, P. ; Fröhlich, F. & Hasenauer, J.: Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis. Bioinformatics 34, 151-159 (2018)
47.
Chlis, N.-K. ; Wolf, F.A. & Theis, F.J.: Model-based branching point detection in single-cell data by K-Branches clustering. Bioinformatics 33, 3211-3219 (2017)
48.
Dirmeier, S.* ; Fuchs, C. ; Müller, N.S. & Theis, F.J.: netReg: Network-regularized linear models for biological association studies. Bioinformatics 34, 896-898 (2017)
49.
Fröhlich, F. ; Theis, F.J. ; Rädler, J.O.* & Hasenauer, J.: Parameter estimation for dynamical systems with discrete events and logical operations. Bioinformatics 33, 1049-1056 (2017)
50.
Hastreiter, M. et al.: KNIME4NGS: A comprehensive toolbox for next generation sequencing analysis. Bioinformatics 33, 1565-1567 (2017)
51.
Hilsenbeck, O.* et al.: fastER: A user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy. Bioinformatics 33, 2020-2028 (2017)
52.
Jaravine, V.* ; Raffegerst, S.* ; Schendel, D.J.* & Frishman, D.: Assessment of cancer and virus antigens for cross-reactivity in human tissues. Bioinformatics 33, 104-111 (2017)
53.
Kazeroonian, A. ; Theis, F.J. & Hasenauer, J.: A scalable moment-closure approximation for large-scale biochemical reaction networks. Bioinformatics 33, i293-i300 (2017)
54.
Ligon, T.S.* et al.: GenSSI 2.0: Multi-experiment structural identifiability analysis of SBML models. Bioinformatics 34, 1421-1423 (2017)
55.
Maier, C. ; Loos, C. & Hasenauer, J.: Robust parameter estimation for dynamical systems from outlier-corrupted data. Bioinformatics 33, 1-8 (2017)
56.
Zheng, J.* et al.: LD Hub: A centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272-279 (2017)
57.
Angerer, P. et al.: Destiny: Diffusion maps for large-scale single-cell data in R. Bioinformatics 32, 1241-1243 (2016)
58.
Geissen, E.M.* et al.: MEMO - multi-experiment mixture model analysis of censored data. Bioinformatics 32, 2464-2472 (2016)
59.
Hross, S. & Hasenauer, J.: Analysis of CFSE time-series data using division-, age- and label-structured population models. Bioinformatics 32, 2321-2329 (2016)
60.
Arnold, M. ; Raffler, J. ; Pfeufer, A. ; Suhre, K. & Kastenmüller, G.: SNiPA: An interactive, genetic variant-centered annotation browser. Bioinformatics 31, 1334-1336 (2015)
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