| Complexity of dopamine metabolism J Meiser, D Weindl, K Hiller Cell Communication and Signaling 11 (1), 34, 2013 | 1014 | 2013 |
| Benchmarking optimization methods for parameter estimation in large kinetic models AF Villaverde, F Fröhlich, D Weindl, J Hasenauer, JR Banga Bioinformatics 35 (5), 830-838, 2019 | 186 | 2019 |
| Simultaneous extraction of proteins and metabolites from cells in culture SC Sapcariu, T Kanashova, D Weindl, J Ghelfi, G Dittmar, K Hiller MethodsX 1, 74-80, 2014 | 181 | 2014 |
| Efficient parameter estimation enables the prediction of drug response using a mechanistic pan-cancer pathway model F Fröhlich, T Kessler, D Weindl, A Shadrin, L Schmiester, H Hache, ... Cell systems 7 (6), 567-579. e6, 2018 | 164 | 2018 |
| How metabolites modulate metabolic flux A Wegner, J Meiser, D Weindl, K Hiller Current opinion in biotechnology 34, 16-22, 2015 | 138 | 2015 |
| PESTO: parameter estimation toolbox P Stapor, D Weindl, B Ballnus, S Hug, C Loos, A Fiedler, S Krause, ... Bioinformatics 34 (4), 705-707, 2018 | 121 | 2018 |
| 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 | 105 | 2021 |
| 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 | 90 | 2021 |
| Community-driven roadmap for integrated disease maps M Ostaszewski, S Gebel, I Kuperstein, A Mazein, A Zinovyev, U Dogrusoz, ... Briefings in bioinformatics 20 (2), 659-670, 2019 | 83 | 2019 |
| Loss of DJ-1 impairs antioxidant response by altered glutamine and serine metabolism J Meiser, S Delcambre, A Wegner, C Jäger, J Ghelfi, AF d'Herouel, ... Neurobiology of disease 89, 112-125, 2016 | 63 | 2016 |
| 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 | 55 | 2023 |
| 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 | 51 | 2020 |
| NTFD—a stand-alone application for the non-targeted detection of stable isotope-labeled compounds in GC/MS data K Hiller, A Wegner, D Weindl, T Cordes, CM Metallo, JK Kelleher, ... Bioinformatics 29 (9), 1226-1228, 2013 | 48 | 2013 |
| Bridging the gap between non-targeted stable isotope labeling and metabolic flux analysis D Weindl, T Cordes, N Battello, SC Sapcariu, X Dong, A Wegner, K Hiller Cancer & metabolism 4 (1), 10, 2016 | 39 | 2016 |
| Fragment formula calculator (FFC): determination of chemical formulas for fragment ions in mass spectrometric data A Wegner, D Weindl, C Jäger, SC Sapcariu, X Dong, G Stephanopoulos, ... Analytical chemistry 86 (4), 2221-2228, 2014 | 37 | 2014 |
| Isotopologue ratio normalization for non-targeted metabolomics D Weindl, A Wegner, C Jäger, K Hiller Journal of chromatography A 1389, 112-119, 2015 | 34 | 2015 |
| Mini-batch optimization enables training of ODE models on large-scale datasets P Stapor, L Schmiester, C Wierling, S Merkt, D Pathirana, BMH Lange, ... Nature communications 13 (1), 34, 2022 | 33 | 2022 |
| BioSimulators: a central registry of simulation engines and services for recommending specific tools B Shaikh, LP Smith, D Vasilescu, G Marupilla, M Wilson, E Agmon, ... Nucleic acids research 50 (W1), W108-W114, 2022 | 31 | 2022 |
| MIA: non-targeted mass isotopolome analysis D Weindl, A Wegner, K Hiller Bioinformatics 32 (18), 2875-2876, 2016 | 27 | 2016 |
| Efficient gradient-based parameter estimation for dynamic models using qualitative data L Schmiester, D Weindl, J Hasenauer Bioinformatics 37 (23), 4493-4500, 2021 | 24 | 2021 |
Jan HasenauerUniversität BonnVerified email at uni-bonn.de
