Yannik Schälte
Yannik Schälte
University of Bonn and Helmholtz Center Munich
Verified email at - Homepage
Cited by
Cited by
PEtab—interoperable specification of parameter estimation problems in systems biology
L Schmiester, Y Schälte, FT Bergmann, T Camba, E Dudkin, J Egert, ...
PLoS computational biology 17 (1), e1008646, 2021
Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich
M Pritsch, K Radon, A Bakuli, R Le Gleut, L Olbrich, ...
AMICI: high-performance sensitivity analysis for large ordinary differential equation models
F Fröhlich, D Weindl, Y Schälte, D Pathirana, Ł Paszkowski, GT Lines, ...
Bioinformatics 37 (20), 3676-3677, 2021
Benchmarking of numerical integration methods for ODE models of biological systems
P Städter, Y Schälte, L Schmiester, J Hasenauer, PL Stapor
Scientific reports 11 (1), 2696, 2021
Efficient parameterization of large-scale dynamic models based on relative measurements
L Schmiester, Y Schälte, F Fröhlich, J Hasenauer, D Weindl
Bioinformatics 36 (2), 594-602, 2020
From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany)
K Radon, A Bakuli, P Pütz, R Le Gleut, JM Guggenbuehl Noller, L Olbrich, ...
BMC infectious diseases 21, 1-15, 2021
Head-to-head evaluation of seven different seroassays including direct viral neutralisation in a representative cohort for SARS-CoV-2
L Olbrich, N Castelletti, Y Schälte, M Garí, P Pütz, A Bakuli, M Pritsch, ...
Journal of General Virology 102 (10), 001653, 2021
Efficient exact inference for dynamical systems with noisy measurements using sequential approximate Bayesian computation
Y Schälte, J Hasenauer
Bioinformatics 36 (Supplement_1), i551–i559, 2020
pyPESTO: a modular and scalable tool for parameter estimation for dynamic models
Y Schälte, F Fröhlich, PJ Jost, J Vanhoefer, D Pathirana, P Stapor, ...
Bioinformatics 39 (11), btad711, 2023
pyABC: Efficient and robust easy-to-use approximate Bayesian computation
Y Schälte, E Klinger, E Alamoudi, J Hasenauer
arXiv preprint arXiv:2203.13043, 2022
Evaluation of derivative-free optimizers for parameter estimation in systems biology
Y Schälte, P Stapor, J Hasenauer
IFAC-PapersOnLine 51 (19), 98-101, 2018
Bayesflow: Amortized bayesian workflows with neural networks
ST Radev, M Schmitt, L Schumacher, L Elsemüller, V Pratz, Y Schälte, ...
arXiv preprint arXiv:2306.16015, 2023
Inferring the effect of interventions on COVID-19 transmission networks
S Syga, D David-Rus, Y Schälte, H Hatzikirou, A Deutsch
Scientific reports 11 (1), 21913, 2021
HCV spread kinetics reveal varying contributions of transmission modes to infection dynamics
K Durso-Cain, P Kumberger, Y Schälte, T Fink, H Dahari, J Hasenauer, ...
Viruses 13 (7), 1308, 2021
A Serology Strategy for Epidemiological Studies Based on the Comparison of the Performance of Seven Different Test Systems-The Representative COVID-19 Cohort Munich
L Olbrich, N Castelletti, Y Schälte, M Gari, P Pütz, A Bakuli, M Pritsch, ...
medRxiv, 2021.01. 13.21249735, 2021
Robust adaptive distance functions for approximate Bayesian inference on outlier-corrupted data
Y Schälte, E Alamoudi, J Hasenauer
bioRxiv, 2021.07. 29.454327, 2021
Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts
L Contento, N Castelletti, E Raimúndez, R Le Gleut, Y Schälte, P Stapor, ...
Epidemics 43, 100681, 2023
The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant
R Le Gleut, M Plank, P Pütz, K Radon, A Bakuli, R Rubio-Acero, ...
BMC Infectious Diseases 23 (1), 466, 2023
FitMultiCell: simulating and parameterizing computational models of multi-scale and multi-cellular processes
E Alamoudi, Y Schälte, R Müller, J Starruß, N Bundgaard, F Graw, ...
Bioinformatics 39 (11), btad674, 2023
Informative and adaptive distances and summary statistics in sequential approximate Bayesian computation
Y Schälte, J Hasenauer
Plos one 18 (5), e0285836, 2023
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