Steffen Klamt
Zeitschriftenartikel (96)
1.
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Designing microbial communities to maximize the thermodynamic driving force for the production of chemicals. PLoS Computational Biology 17 (6), e1009093 (2021)
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Increasing ATP turnover boosts productivity of 2,3-butanediol synthesis in Escherichia coli. Microbial Cell Factories 20, 63 (2021)
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Cell‐free multi‐enzyme synthesis and purification of uridine diphosphate galactose. Chembiochem (2021)
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Blending industrial blast furnace gas with H 2 enables Acetobacterium woodii to efficiently co-utilize CO, CO2 and H2. Bioresource Technology 323, 124573 (2021)
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Systematizing the different notions of growth-coupled product synthesis and a single framework for computing corresponding strain designs. Biotechnology Journal, 2100236 (2021)
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Automatic construction of metabolic models with enzyme constraints. BMC Bioinformatics 21, 19 (2020)
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MEMO: A Method for Computing Metabolic Modules for Cell-Free Production Systems. ACS Synthetic Biology 9 (3), S. 556 - 566 (2020)
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Speeding up the core algorithm for the dual calculation of minimal cut sets in large metabolic networks. BMC Bioinformatics (21), 510 (2020)
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MEMOTE for standardized genome-scale metabolic model testing. Nature Biotechnology 38, S. 272 - 276 (2020)
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An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets. PLoS Computational Biology 16 (7), e1008110 (2020)
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ATPase-based implementation of enforced ATP wasting in Saccharomyces cerevisiae for improved ethanol production. Biotechnology for Biofuels (13), 185 (2020)
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Broadening the Scope of Enforced ATP Wasting as a Tool for Metabolic Engineering in Escherichia coli. Biotechnology Journal 14 (9), 1800438 (2019)
13.
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Computergestütztes Design mikrobieller Zellfabriken. Biospektrum 25 (2), S. 156 - 158 (2019)
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RedCom: A strategy for reduced metabolic modeling of complex microbial communities and its application for analyzing experimental datasets from anaerobic digestion. PLoS Computational Biology 15 (2), e1006759 (2019)
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Characterizing and Ranking Computed Metabolic Engineering Strategies. Bioinformatics 35 (17), S. 3063 - 3072 (2019)
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Designing optimal experiments to discriminate interaction graph models. IEEE ACM Transactions on Computational Biology and Bioinformatics 16 (3), S. 925 - 935 (2019)
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Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity. Frontiers in Microbiology 10, 1095 (2019)
18.
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Generalizing diffuse interface methods on graphs: non-smooth potentials and hypergraphs. SIAM Journal on Applied Mathematics 78 (3), S. 1350 - 1377 (2018)
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OptMDFpathway: Identification of metabolic pathways with maximal thermodynamic driving force and its application for analyzing the endogenous CO2 fixation potential of Escherichia coli. PLoS Computational Biology 14 (9), e1006492 (2018)
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Temperature-dependent dynamic control of the TCA cycle increases volumetric productivity of itaconic acid production by Escherichia coli. Biotechnology and Bioengineering 115 (1), S. 156 - 164 (2018)
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When do two-stage processes outperform one-stage processes? Biotechnology Journal 13 (2), 1700539 (2018)
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A mathematical framework for yield (versus rate) optimization in constraint-based modeling and applications in metabolic engineering. Metabolic Engineering 47, S. 153 - 169 (2018)
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Establishment of a five-enzyme cell-free cascade for the synthesis of uridine diphosphate N-acetylglucosamine. Journal of Biotechnology 283, S. 120 - 129 (2018)
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MoVE identifies metabolic valves to switch between phenotypic states. Nature Communications 9, 5332 (2018)
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EColiCore2: a reference model of the central metabolism of Escherichia coli and the relationships to its genome-scale parent model. Scientific Reports 7, 39647 (2017)
26.
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Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms. Nature Communications 8, 15926 (2017)
27.
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Use of CellNetAnalyzer in biotechnology and metabolic engineering. Journal of Biotechnology 261, S. 221 - 228 (2017)
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From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints. PLoS Computational Biology 13 (4), e1005409 (2017)
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Exact quantification of cellular robustness in genome-scale metabolic networks. Bioinformatics 32 (5), S. 730 - 737 (2016)
30.
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Model-Based metabolic engineering enables high yield itaconic acid production by Escherichia coli. Metabolic Engineering 38, S. 29 - 37 (2016)
31.
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Predicting compositions of microbial communities from stoichiometric models with applications for the biogas process. Biotechnology for Biofuels 9, 17 (2016)
32.
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TRaCE+: Ensemble inference of gene regulatory networks from transcriptional expression profiles of gene knock-out experiments. BMC Bioinformatics 17 (17), 252 (2016)
33.
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MUFINS: multi-formalism interaction network simulator. npj Systems Biology and Applications 2, 16032 (2016)
34.
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Silence on the relevant literature and errors in implementation. Nature Biotechnology 33 (4), S. 336 - 339 (2015)
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Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling. PLoS Computational Biology 11 (4), e1004192 (2015)
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An algorithm for the reduction of genome-scale metabolic network models to meaningful core models. BMC Systems Biology 9, 48 (2015)
37.
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Enforced ATP futile cycling increases specific productivity and yield of anaerobic lactate production in Escherichia coli. Biotechnology and Bioengineering 112 (10), S. 2195 - 2199 (2015)
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Manipulation of the ATP pool as a tool for metabolic engineering. Biochemical Society Transactions (London) 43 (6), S. 1140 - 1145 (2015)
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On the feasibility of growth-coupled product synthesis in microbial strains. Metabolic Engineering 30, S. 166 - 178 (2015)
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Genome-scale strain designs based on regulatory minimal cut sets. Bioinformatics 31 (17), S. 2844 - 2851 (2015)
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Network-Based Analysis of Nutraceuticals in Human Hepatocellular Carcinomas Reveals Mechanisms of Chemopreventive Action. CPT: Pharmacometrics & Systems Pharmacology 4 (6), S. 350 - 361 (2015)
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T160‐phosphorylated CDK2 defines threshold for HGF‐dependent proliferation in primary hepatocytes. Molecular Systems Biology 11, 795 (2015)
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Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies. BMC Bioinformatics 16 (1), 345 (2015)
44.
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Computational Systems Biology — neues Fach in den Lebenswissenschaften. Biospektrum 21 (1), S. 46 - 48 (2015)
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Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling. Microbial Cell Factories 13, S. 128 - 128 (2014)
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Enumeration of Smallest Intervention Strategies in Genome-Scale Metabolic Networks. PLoS Computational Biology 10 (1), e1003378 (2014)
47.
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The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis. BMC Biotechnology 14, S. 72 (2014)
48.
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A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models. Biosystems 124, S. 26 - 38 (2014)
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SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formlisms and tools. BMC Systems Biology 7, S. 135 (2013)
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An effective framework for reconstructing gene regulatory networks from genetical genomics data. Bioinformatics 29 (2), S. 246 - 254 (2013)
51.
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Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models. Molecular BioSystems 9 (7), S. 1576 - 1583 (2013)
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In silico profiling of Escherichia coli and Saccharomyces cerevisiae as terpenoid factories. Microbial Cell Factories 12, 84 (2013)
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Evaluating differences of metabolic performances: Statistical methods and their application to animal cell cultivations. Biotechnology and Bioengineering 110 (10), S. 2633 - 2642 (2013)
54.
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Comparison and improvement of algorithms for computing minimal cut sets. BMC Bioinformatics 14 (1), S. 318 (2013)
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Detecting and Removing Inconsistencies between Experimental Data and Signaling Network Topologies Using Integer Linear Programming on Interaction Graphs. PLoS Computational Biology 9 (9), S. e1003204 (2013)
56.
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Reconstruction of large-scale regulatory networks based on perturbation graphs and transitive reduction: improved methods and their evaluation. BMC Systems Biology 7, S. 73 (2013)
57.
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Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks. Cell Communication and Signaling 11 (1), S. 43 (2013)
58.
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Minimal cut sets in metabolic networks are elementary modes in a dual network. Bioinformatics 28 (3), S. 381 - 387 (2012)
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An integrative model links multiple inputs and signaling pathways to the onset of DNA synthesis in hepatocytes. FEBS Journal 279 (18), S. 3290 - 3313 (2012)
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Metabolic network modeling of redox balancing and biohydrogen production in purple nonsulfur bacteria. BMC Systems Biology 5, S. 150 (2011)
61.
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Computing complex metabolic intervention strategies using constrained minimal cut sets. Metabolic Engineering 13 (2), S. 204 - 213 (2011)
62.
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An application programming interface for CellNetAnalyzer. Biosystems 105 (2), S. 162 - 168 (2011)
63.
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Large-scale models of IL-1 and IL-6 signaling and their hepatocellular specification. Molecular BioSystems 7 (12), S. 3253 - 3270 (2011)
64.
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From Binary to Multivalued to Continuous Models: The Iac Operon as a Case Study. Journal of Integrative Bioinformatics 7 (1), S. 151 (2010)
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CASOP: a computational approach for strain optimization aiming at high productivity. Journal of Biotechnology 147 (2), S. 88 - 101 (2010)
66.
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TRANSWESD: inferring cellular networks with transitive reduction. Bioinformatics 26 (17), S. 2160 - 2168 (2010)
67.
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Computing Combinatorial Intervention Strategies and Failure Modes in Signaling Networks. Journal of Computational Biology 17 (1), S. 39 - 53 (2010)
68.
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Hypergraphs and cellular networks. PLoS Computational Biology 5 (5), S. e1000385 (2009)
69.
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Computing Paths and Cycles in Biological Interaction Graphs. BMC Bioinformatics 10, S. 181 (2009)
70.
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Logical network of genotoxic stress-induced NF-kB signal transduction predicts putative target structures for therapeutic intervention strategies. Advances and Applications in Bioinformatics and Chemistry 2, S. 125 - 138 (2009)
71.
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Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction. Molecular Systems Biology 5, S. 331 (2009)
72.
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The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. PLoS Computational Biology 5 (8), e1000438 (2009)
73.
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Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling. BMC Systems Biology 3, 98 (2009)
74.
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Host-pathogen systems biology: Logical modelling of hepatocyte growth factor and Helicobacter pylori induced c-Met signal transduction. BMC Systems Biology 2, 4 (2008)
75.
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Computing knock-out strategies in metabolic networks. Journal of Computational Biology 15 (3), S. 259 - 268 (2008)
76.
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Modeling the electron transport chain of purple non-sulfur bacteria. Molecular Systems Biology 4, 156 (2008)
77.
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Multistability of signal transduction motifs. IET Systems Biology 2 (2), S. 80 - 93 (2008)
78.
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GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism. Genome Biology 8, R89 (2007)
79.
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Structural and functional analysis of cellular networks with CellNetAnalyzer. BMC Systems Biology 1, 2 (2007)
80.
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A logical model provides insights into T cell receptor signaling. PLoS Computational Biology 3, e163 (2007)
81.
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Generalized concept of minimal cut sets in biochmical networks. Biosystems 83 (2-3 ), S. 233 - 247 (2006)
82.
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A methodology for the structural and functional analysis of signaling and regulatory networks. BMC Bioinformatics 7, S. 56 (2006)
83.
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Visual set-up of logical models of signaling and regulatory networks with ProMoT. BMC Bioinformatics 7, 506 (2006)
84.
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Algorithmic approaches for computing elementary modes in large biochemical reaction networks. IEE Proceedings - Systems Biology 152 (4), S. 249 - 255 (2005)
85.
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Computation of elementary modes: a unifying framework and the new binary approach. BMC Bioinformatics 5, 175 (2004)
86.
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Minimal cut sets in biochemical reaction networks. Bioinformatics 20, S. 226 - 234 (2004)
87.
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Workbench zur Modellbildung, Simulation und Analyse zellulärer Systeme. it - Information Technology 46, S. 12 - 19 (2004)
88.
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Comparison of network-based pathway analysis methods. Trends in Biotechnology 22 (8), S. 400 - 405 (2004)
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Two approaches for metabolic pathway analysis? Trends in Biotechnology 21 (2), S. 64 - 69 (2003)
90.
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FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics 19 (2), S. 261 - 269 (2003)
91.
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Calculating as many fluxes as possible in underdetermined metabolic networks. Molecular Biology Reports 29 (1-2), S. 243 - 248 (2002)
92.
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Calculability analysis in underdetermined metabolic networks illustrated by a model of the central metabolism in purple nonsulfur bacteria. Biotechnology and Bioengineering 77 (7), S. 734 - 751 (2002)
93.
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Combinatorial complexity of pathway analysis in metabolic networks. Molecular Biology Reports 29 (1-2), S. 233 - 236 (2002)
94.
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Applying metabolic pathway analysis to make good use of methanol. Trends in Biotechnology 20 (8), S. 322 (2002)
95.
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Use of network analysis of metabolic systems in bioengineering. Bioprocess and Biosystems Engineering 24 (6), S. 363 - 372 (2002)
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Metabolic network structure determines key aspects of functionality and regulation. Nature 420 (6912), S. 190 - 193 (2002)
Buchkapitel (3)
97.
Buchkapitel
Stoichiometric and Constraint-Based Analysis of Biochemical Reaction Networks. In: Large-Scale Networks in Engineering and Life Sciences, S. 263 - 316. Springer International Publishing, Cham (2014)
98.
Buchkapitel
Benchmarking a Simple Yet Effective Approach for Inferring Gene Regulatory Networks from Systems Genetic Data. In: Gene Network Inference: Verification of Methods for Systems Genetic Data., S. 33 - 47. Springer, Heidelberg (2013)
99.
Buchkapitel
Host-pathogen interactions. In: Systems Biology of Tuberculosis, S. 107 - 126. Springer, New York (2013)