Daniel Weindl

发表

Complexity of dopamine metabolism

Daniel Weindl, Karsten Hiller, K. Hiller, 2013, Cell Communication and Signaling.

BioSimulators: a central registry of simulation engines and services for recommending specific tools

Jonathan R. Karr, Frank T. Bergmann, Ryan K. Spangler, 2022, Nucleic Acids Res..

LNA++: Linear Noise Approximation with First and Second Order Sensitivities

Fabian J. Theis, Jan Hasenauer, Carsten Marr, 2018, CMSB.

Community-driven roadmap for integrated disease maps

Marek Ostaszewski, Stephan Gebel, Inna Kuperstein, 2018, Briefings Bioinform..

AMICI: high-performance sensitivity analysis for large ordinary differential equation models

J. Hasenauer, P. Stapor, D. Weindl, 2020, Bioinform..

Parameterization of mechanistic models from qualitative data using an efficient optimal scaling approach

Daniel Weindl, Leonard Schmiester, Jan Hasenauer, 2020, Journal of Mathematical Biology.

Statistical inference of mechanistic models from qualitative data using an efficient optimal scaling approach

Leonard Schmiester, Daniel Weindl, Jan Hasenauer, 2019, bioRxiv.

Benchmarking optimization methods for parameter estimation in large kinetic models

Julio R. Banga, Jan Hasenauer, Daniel Weindl, 2018, bioRxiv.

Bridging the gap between non-targeted stable isotope labeling and metabolic flux analysis

Sean C. Sapcariu, N. Battello, K. Hiller, 2016, Cancer & metabolism.

Non-targeted Tracer Fate Detection.

K. Hiller, D. Weindl, A. Wegner, 2015, Methods in enzymology.

Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networks

J. Hasenauer, P. Stapor, D. Weindl, 2022, bioRxiv.

Simultaneous extraction of proteins and metabolites from cells in culture

Sean C. Sapcariu, G. Dittmar, K. Hiller, 2014, MethodsX.

Efficient gradient-based parameter estimation for dynamic models using qualitative data

J. Hasenauer, D. Weindl, Leonard Schmiester, 2021, bioRxiv.

Mini-batch optimization enables training of ODE models on large-scale datasets

Paul Stapor, Leonard Schmiester, Christoph Wierling, 2019, Nature Communications.

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

Daniel Weindl, Jan Hasenauer, Leonard Schmiester, 2019, bioRxiv.

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

Daniel Weindl, Matthias Heinig, Jan Hasenauer, 2018, Cell systems.

Efficient computation of steady states in large-scale ODE models of biochemical reaction networks

Leonard Schmiester, Daniel Weindl, Jan Hasenauer, 2019, IFAC-PapersOnLine.

Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells

David R. Penas, Paul F. Lang, B. Novák, 2023, bioRxiv.

MIA: non-targeted mass isotopolome analysis

Daniel Weindl, Karsten Hiller, André Wegner, 2016, Bioinform..

Chapter 60 Repetitive transcranial magnetic stimulation in Parkinson's disease and focal dystonia

H. Siebner, B. Conrad, D. Weindl, 2002 .

Fragment formula calculator (FFC): determination of chemical formulas for fragment ions in mass spectrometric data.

Gregory Stephanopoulos, Daniel Weindl, Karsten Hiller, 2014, Analytical chemistry.

Isotopologue ratio normalization for non-targeted metabolomics.

K. Hiller, D. Weindl, A. Wegner, 2015, Journal of chromatography. A.

Isotope cluster-based compound matching in gas chromatography/mass spectrometry for non-targeted metabolomics.

Sean C. Sapcariu, K. Hiller, D. Weindl, 2013, Analytical chemistry.

NTFD—a stand-alone application for the non-targeted detection of stable isotope-labeled compounds in GC/MS data

Gregory Stephanopoulos, Daniel Weindl, Karsten Hiller, 2013, Bioinform..

PESTO: Parameter EStimation TOolbox

Jan Hasenauer, Paul Stapor, Daniel Weindl, 2017, Bioinform..

How metabolites modulate metabolic flux.

Daniel Weindl, Karsten Hiller, K. Hiller, 2015, Current opinion in biotechnology.

Efficient parameterization of large-scale mechanistic models enables drug response prediction for cancer cell lines

Fabian J Theis, J. Hasenauer, H. Lehrach, 2017, bioRxiv.

Loss of DJ-1 impairs antioxidant response by altered glutamine and serine metabolism

W. Wurst, R. Krüger, M. Leist, 2016, Neurobiology of Disease.

Metabolome-Wide Analysis of Stable Isotope Labeling—Is It Worth the Effort?

K. Hiller, D. Weindl, A. Wegner, 2015, Front. Physiol..

A more expressive spline representation for SBML models improves code generation performance in AMICI

J. Hasenauer, P. Stapor, L. Contento, 2023, bioRxiv.

Dynamic models for metabolomics data integration

Daniel Weindl, Polina Lakrisenko, D. Weindl, 2021, 2105.10365.

pyPESTO: a modular and scalable tool for parameter estimation for dynamic models

J. Hasenauer, P. Stapor, E. Dudkin, 2023, Bioinform..