Daniel C. Zielinski
Daniel C. Zielinski
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Cited by
Cited by
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2. 0
J Schellenberger, R Que, RMT Fleming, I Thiele, JD Orth, AM Feist, ...
Nature protocols 6 (9), 1290-1307, 2011
Recon3D enables a three-dimensional view of gene variation in human metabolism
E Brunk, S Sahoo, DC Zielinski, A Altunkaya, A Dräger, N Mih, F Gatto, ...
Nature biotechnology 36 (3), 272-281, 2018
Recon 2.2: from reconstruction to model of human metabolism
N Swainston, K Smallbone, H Hefzi, PD Dobson, J Brewer, M Hanscho, ...
Metabolomics 12, 1-7, 2016
Model-driven evaluation of the production potential for growth-coupled products of Escherichia coli
AM Feist, DC Zielinski, JD Orth, J Schellenberger, MJ Herrgard, ...
Metabolic engineering 12 (3), 173-186, 2010
A consensus genome-scale reconstruction of Chinese hamster ovary cell metabolism
H Hefzi, KS Ang, M Hanscho, A Bordbar, D Ruckerbauer, M Lakshmanan, ...
Cell systems 3 (5), 434-443. e8, 2016
A systematic evaluation of methods for tailoring genome-scale metabolic models
S Opdam, A Richelle, B Kellman, S Li, DC Zielinski, NE Lewis
Cell systems 4 (3), 318-329. e6, 2017
Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models
D Heckmann, CJ Lloyd, N Mih, Y Ha, DC Zielinski, ZB Haiman, ...
Nature communications 9 (1), 5252, 2018
Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic …
C Zuñiga, CT Li, T Huelsman, J Levering, DC Zielinski, BO McConnell, ...
Plant physiology 172 (1), 589-602, 2016
Personalized whole-cell kinetic models of metabolism for discovery in genomics and pharmacodynamics
A Bordbar, D McCloskey, DC Zielinski, N Sonnenschein, N Jamshidi, ...
Cell systems 1 (4), 283-292, 2015
Systems biology analysis of drivers underlying hallmarks of cancer cell metabolism
DC Zielinski, N Jamshidi, AJ Corbett, A Bordbar, A Thomas, BO Palsson
Scientific reports 7 (1), 41241, 2017
A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks
H Nam, M Campodonico, A Bordbar, DR Hyduke, S Kim, DC Zielinski, ...
PLoS computational biology 10 (9), e1003837, 2014
Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks
JT Yurkovich, DC Zielinski, L Yang, G Paglia, O Rolfsson, ...
Journal of Biological Chemistry 292 (48), 19556-19564, 2017
Pharmacogenomic and clinical data link non-pharmacokinetic metabolic dysregulation to drug side effect pathogenesis
DC Zielinski, FV Filipp, A Bordbar, K Jensen, JW Smith, MJ Herrgard, ...
Nature communications 6 (1), 7101, 2015
COBRA Toolbox 2.0
D Hyduke, J Schellenberger, R Que, R Fleming, I Thiele, J Orth, A Feist, ...
Temperature-dependent estimation of Gibbs energies using an updated group-contribution method
B Du, Z Zhang, S Grubner, JT Yurkovich, BO Palsson, DC Zielinski
Biophysical journal 114 (11), 2691-2702, 2018
Predicting outcomes of steady-state 13C isotope tracing experiments using Monte Carlo sampling
J Schellenberger, DC Zielinski, W Choi, S Madireddi, V Portnoy, DA Scott, ...
BMC systems biology 6, 1-14, 2012
Evaluation of rate law approximations in bottom-up kinetic models of metabolism
B Du, DC Zielinski, ES Kavvas, A Dräger, J Tan, Z Zhang, KE Ruggiero, ...
BMC systems biology 10, 1-15, 2016
Thermodynamic favorability and pathway yield as evolutionary tradeoffs in biosynthetic pathway choice
B Du, DC Zielinski, JM Monk, BO Palsson
Proceedings of the National Academy of Sciences 115 (44), 11339-11344, 2018
SBMLsqueezer 2: context-sensitive creation of kinetic equations in biochemical networks
A Dräger, DC Zielinski, R Keller, M Rall, J Eichner, BO Palsson, A Zell
BMC systems biology 9, 1-17, 2015
MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics
ZB Haiman, DC Zielinski, Y Koike, JT Yurkovich, BO Palsson
PLoS computational biology 17 (1), e1008208, 2021
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