Daniel Weindl
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Explore the profile of Daniel Weindl including associated specialties, affiliations and a list of published articles.
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27
Citations
771
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Recent Articles
1.
Lakrisenko P, Pathirana D, Weindl D, Hasenauer J
PLoS One
. 2024 Oct;
19(10):e0312148.
PMID: 39441813
Estimating parameters of dynamic models from experimental data is a challenging, and often computationally-demanding task. It requires a large number of model simulations and objective function gradient computations, if gradient-based...
2.
Lang P, Penas D, Banga J, Weindl D, Novak B
PLoS Comput Biol
. 2024 Jan;
20(1):e1011151.
PMID: 38190398
The mammalian cell cycle is regulated by a well-studied but complex biochemical reaction system. Computational models provide a particularly systematic and systemic description of the mechanisms governing mammalian cell cycle...
3.
Schalte Y, Frohlich F, Jost P, Vanhoefer J, Pathirana D, Stapor P, et al.
Bioinformatics
. 2023 Nov;
39(11).
PMID: 37995297
Summary: Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex...
4.
Lakrisenko P, Stapor P, Grein S, Paszkowski L, Pathirana D, Frohlich F, et al.
PLoS Comput Biol
. 2023 Jan;
19(1):e1010783.
PMID: 36595539
Dynamical models in the form of systems of ordinary differential equations have become a standard tool in systems biology. Many parameters of such models are usually unknown and have to...
5.
Streibl B, Lahne H, Grahl A, Agsten P, Bichler M, Buchl C, et al.
Microorganisms
. 2022 Sep;
10(9).
PMID: 36144413
Background: Despite a vaccination rate of 82.0% (n = 123/150), a SARS-CoV-2 (Alpha) outbreak with 64.7% (n = 97/150) confirmed infections occurred in a nursing home in Bavaria, Germany. Objective:...
6.
BioSimulators: a central registry of simulation engines and services for recommending specific tools
Shaikh B, Smith L, Vasilescu D, Marupilla G, Wilson M, Agmon E, et al.
Nucleic Acids Res
. 2022 May;
50(W1):W108-W114.
PMID: 35524558
Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating...
7.
Stapor P, Schmiester L, Wierling C, Merkt S, Pathirana D, Lange B, et al.
Nat Commun
. 2022 Jan;
13(1):34.
PMID: 35013141
Quantitative dynamic models are widely used to study cellular signal processing. A critical step in modelling is the estimation of unknown model parameters from experimental data. As model sizes and...
8.
Schmiester L, Weindl D, Hasenauer J
Bioinformatics
. 2021 Jul;
37(23):4493-4500.
PMID: 34260697
Motivation: Unknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative...
9.
Frohlich F, Weindl D, Schalte Y, Pathirana D, Paszkowski L, Lines G, et al.
Bioinformatics
. 2021 Apr;
37(20):3676-3677.
PMID: 33821950
Summary: Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can...
10.
Schmiester L, Schalte Y, Bergmann F, Camba T, Dudkin E, Egert J, et al.
PLoS Comput Biol
. 2021 Jan;
17(1):e1008646.
PMID: 33497393
Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been-so far-no broadly supported format for the specification of parameter estimation problems in systems biology....