| Intracellular Mycobacterium tuberculosis exploits multiple host nitrogen sources during growth in human macrophages K Borah, M Beyß, A Theorell, H Wu, P Basu, TA Mendum, K Nӧh, ... Cell reports 29 (11), 3580-3591. e4, 2019 | 75 | 2019 |
| Current state and challenges for dynamic metabolic modeling E Vasilakou, D Machado, A Theorell, I Rocha, K Nöh, M Oldiges, SA Wahl Current opinion in microbiology 33, 97-104, 2016 | 59 | 2016 |
| To be certain about the uncertainty: Bayesian statistics for 13C metabolic flux analysis A Theorell, S Leweke, W Wiechert, K Nöh Biotechnology and bioengineering 114 (11), 2668-2684, 2017 | 33 | 2017 |
| Reversible jump MCMC for multi-model inference in Metabolic Flux Analysis A Theorell, K Nöh Bioinformatics 36 (1), 232-240, 2020 | 22 | 2020 |
| HOPS: high-performance library for (non-) uniform sampling of convex-constrained models JF Jadebeck, A Theorell, S Leweke, K Nöh Bioinformatics 37 (12), 1776-1777, 2021 | 19 | 2021 |
| Determination of essential phenotypic elements of clusters in high-dimensional entities—DEPECHE A Theorell, YT Bryceson, J Theorell PLoS One 14 (3), e0203247, 2019 | 19 | 2019 |
| When a single lineage is not enough: uncertainty-aware tracking for spatio-temporal live-cell image analysis A Theorell, J Seiffarth, A Grünberger, K Nöh Bioinformatics 35 (7), 1221-1228, 2019 | 16 | 2019 |
| PolyRound: polytope rounding for random sampling in metabolic networks A Theorell, JF Jadebeck, K Nöh, J Stelling Bioinformatics 38 (2), 566-567, 2022 | 12 | 2022 |
| One‐shot 13C15N‐metabolic flux analysis for simultaneous quantification of carbon and nitrogen flux K Borah Slater, M Beyß, Y Xu, J Barber, C Costa, J Newcombe, A Theorell, ... Molecular systems biology 19 (3), e11099, 2023 | 11 | 2023 |
| Metabolic networks, microbial consortia, and analogies to smart grids A Theorell, J Stelling Proceedings of the IEEE 110 (5), 541-556, 2022 | 9 | 2022 |
| Intracellular Mycobacterium tuberculosis exploits multiple host nitrogen sources during growth in human macrophages. Cell Rep 29: 3580–3591 K Borah, M Beyß, A Theorell, H Wu, P Basu, TA Mendum, K Nöh, ... | 6 | 2019 |
| Bayesian multi-model-based 13C15N-metabolic flux analysis quantifies carbon-nitrogen metabolism in mycobacteria K Borah, M Beyß, Y Xu, J Barber, C Costa, J Newcombe, A Theorell, ... bioRxiv, 2022.03. 08.483448, 2022 | 4 | 2022 |
| Assumptions on decision making and environment can yield multiple steady states in microbial community models A Theorell, J Stelling BMC bioinformatics 24 (Suppl 1), 262, 2023 | 3 | 2023 |
| Model uncertainty analysis for metabolic network inference: a case study in bayesian model averaging A Theorell, K Nöh IFAC-PapersOnLine 51 (19), 124-125, 2018 | 3 | 2018 |
| Microbial community decision making models in batch and chemostat cultures A Theorell, J Stelling Computational Methods in Systems Biology: 19th International Conference …, 2021 | 2 | 2021 |
| A mixed nitrogen diet and compartmentalized utilization for Mycobacterium tuberculosis replicating in host cells: results of a systems-based analysis K Borah, M Beyß, A Theorell, H Wu, P Basu, T Mendum, K Noh, D Beste, ... bioRxiv, 542480, 2019 | 2 | 2019 |
| Towards a mechanistic understanding of factors controlling the stereoselectivity of transketolase A Baierl, A Theorell, U Mackfeld, P Marquardt, F Hoffmann, S Moers, ... ChemCatChem 10 (12), 2601-2611, 2018 | 2 | 2018 |
| Bayesian methods for data-driven characterization of cells A Theorell, W Wiechert, J Stelling Lehrstuhl für Computational Systems Biotechnology (FZ Jülich), 2020 | 1 | 2020 |
| Rethinking 13C-metabolic flux analysis–The Bayesian way of flux inference A Theorell, JF Jadebeck, W Wiechert, J McFadden, K Nöh Metabolic Engineering 83, 137-149, 2024 | | 2024 |
| Scalable enumeration and sampling of minimal metabolic pathways for organisms and communities O Øyås, A Theorell, J Stelling bioRxiv, 2024.10. 09.617357, 2024 | | 2024 |
