Pseudo-transition Analysis Identifies the Key Regulators of Dynamic Metabolic Adaptations from Steady-State Data.
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U. Sauer | E. Noor | K. Kochanowski | Luca Gerosa | Dimitris Christodoulou | Bart R B Haverkorn van Rijsewijk | T. S. Schmidt | Karl Kochanowski
[1] W. Wiechert,et al. Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems. , 1999, Biotechnology and bioengineering.
[2] J. Nielsen,et al. Quantitative analysis of metabolic fluxes in Escherichia coli, using two-dimensional NMR spectroscopy and complete isotopomer models. , 1999, Journal of biotechnology.
[3] H. Bremer. Modulation of Chemical Composition and Other Parameters of the Cell by Growth Rate , 1999 .
[4] D. Botstein,et al. Genomic expression programs in the response of yeast cells to environmental changes. , 2000, Molecular biology of the cell.
[5] Chiara Sabatti,et al. Network component analysis: Reconstruction of regulatory signals in biological systems , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[6] Markus J. Herrgård,et al. Integrating high-throughput and computational data elucidates bacterial networks , 2004, Nature.
[7] Katy C. Kao,et al. Transcriptome-based determination of multiple transcription regulator activities in Escherichia coli by using network component analysis. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[8] J. Nielsen,et al. Uncovering transcriptional regulation of metabolism by using metabolic network topology. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[9] J. Heijnen,et al. Revisiting the 13C‐label distribution of the non‐oxidative branch of the pentose phosphate pathway based upon kinetic and genetic evidence , 2005, The FEBS journal.
[10] J. Heijnen,et al. Metabolic-flux analysis of Saccharomyces cerevisiae CEN.PK113-7D based on mass isotopomer measurements of (13)C-labeled primary metabolites. , 2005, FEMS yeast research.
[11] Barbara M. Bakker,et al. Unraveling the complexity of flux regulation: A new method demonstrated for nutrient starvation in Saccharomyces cerevisiae , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[12] U. Sauer,et al. Article number: 62 REVIEW Metabolic networks in motion: 13 C-based flux analysis , 2022 .
[13] U. Alon,et al. A comprehensive library of fluorescent transcriptional reporters for Escherichia coli , 2006, Nature Methods.
[14] Pei Yee Ho,et al. Multiple High-Throughput Analyses Monitor the Response of E. coli to Perturbations , 2007, Science.
[15] Barbara M. Bakker,et al. The fluxes through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscriptional levels , 2007, Proceedings of the National Academy of Sciences.
[16] Matthew J. Brauer,et al. Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. , 2008, Molecular biology of the cell.
[17] U. Sauer,et al. Identification of furfural as a key toxin in lignocellulosic hydrolysates and evolution of a tolerant yeast strain , 2008, Microbial biotechnology.
[18] U. Alon,et al. Diverse two-dimensional input functions control bacterial sugar genes. , 2008, Molecular cell.
[19] B. Görke,et al. Carbon catabolite repression in bacteria: many ways to make the most out of nutrients , 2008, Nature Reviews Microbiology.
[20] T. Hwa,et al. Growth Rate-Dependent Global Effects on Gene Expression in Bacteria , 2009, Cell.
[21] Joerg M. Buescher,et al. Metabolic Fluxes during Strong Carbon Catabolite Repression by Malate in Bacillus subtilis* , 2009, The Journal of Biological Chemistry.
[22] Jie Yuan,et al. Achieving Optimal Growth through Product Feedback Inhibition in Metabolism , 2010, PLoS Comput. Biol..
[23] U. Sauer,et al. Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast , 2010, Molecular systems biology.
[24] U. Alon,et al. Protein Dynamics in Drug Combinations: a Linear Superposition of Individual-Drug Responses , 2010, Cell.
[25] Joerg M. Buescher,et al. Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. , 2010, Analytical chemistry.
[26] U. Sauer,et al. Systems biology of microbial metabolism. , 2010, Current opinion in microbiology.
[27] U. Sauer,et al. Regulation and control of metabolic fluxes in microbes. , 2011, Current opinion in biotechnology.
[28] U. Sauer,et al. Large-scale 13C-flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli , 2011, Molecular systems biology.
[29] A. Ishihama,et al. Novel Members of the Cra Regulon Involved in Carbon Metabolism in Escherichia coli , 2010, Journal of Bacteriology.
[30] N. Fujita,et al. Novel Roles of cAMP Receptor Protein (CRP) in Regulation of Transport and Metabolism of Carbon Sources , 2011, PloS one.
[31] Ronan M. T. Fleming,et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 , 2007, Nature Protocols.
[32] David H Perlman,et al. Regulation of yeast pyruvate kinase by ultrasensitive allostery independent of phosphorylation. , 2012, Molecular cell.
[33] U. Sauer,et al. Regulation of yeast central metabolism by enzyme phosphorylation , 2012, Molecular systems biology.
[34] Matthias Heinemann,et al. Functioning of a metabolic flux sensor in Escherichia coli , 2012, Proceedings of the National Academy of Sciences.
[35] Joerg M. Buescher,et al. Global Network Reorganization During Dynamic Adaptations of Bacillus subtilis Metabolism , 2012, Science.
[36] Julio Collado-Vides,et al. RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more , 2012, Nucleic Acids Res..
[37] Ronan M. T. Fleming,et al. Consistent Estimation of Gibbs Energy Using Component Contributions , 2013, PLoS Comput. Biol..
[38] R. Milo,et al. A note on the kinetics of enzyme action: A decomposition that highlights thermodynamic effects , 2013, FEBS letters.
[39] U. Sauer,et al. Dissecting specific and global transcriptional regulation of bacterial gene expression , 2013, Molecular systems biology.
[40] T. Hwa,et al. Coordination of bacterial proteome with metabolism by cyclic AMP signalling , 2013, Nature.
[41] Barbara M. Bakker,et al. A new regulatory principle for in vivo biochemistry: Pleiotropic low affinity regulation by the adenine nucleotides – Illustrated for the glycolytic enzymes of Saccharomyces cerevisiae , 2013, FEBS letters.
[42] Kelly M. Wetmore,et al. Indirect and suboptimal control of gene expression is widespread in bacteria , 2013, Molecular systems biology.
[43] J. Stelling,et al. Transcriptional regulation is insufficient to explain substrate-induced flux changes in Bacillus subtilis , 2013, Molecular systems biology.
[44] R. Milo,et al. Promoters maintain their relative activity levels under different growth conditions , 2013, Molecular systems biology.
[45] U. Sauer,et al. Systematic identification of allosteric protein-metabolite interactions that control enzyme activity in vivo , 2013, Nature Biotechnology.
[46] Uri Alon,et al. Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions , 2014, PLoS Comput. Biol..
[47] U. Sauer,et al. Coordination of microbial metabolism , 2014, Nature Reviews Microbiology.
[48] Wolfram Liebermeister,et al. Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism , 2014, PLoS Comput. Biol..
[49] U. Sauer,et al. Advancing metabolic models with kinetic information. , 2014, Current opinion in biotechnology.
[50] D. Amador-Noguez,et al. Post-translational modifications as key regulators of bacterial metabolic fluxes. , 2015, Current opinion in microbiology.
[51] David W. Erickson,et al. Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria , 2015, Molecular systems biology.
[52] N. Kruger,et al. Fluxes through plant metabolic networks: measurements, predictions, insights and challenges. , 2015, The Biochemical journal.