| Year |
Citation |
Score |
| 2023 |
Bekiaris PS, Klamt S. Network-wide thermodynamic constraints shape NAD(P)H cofactor specificity of biochemical reactions. Nature Communications. 14: 4660. PMID 37537166 DOI: 10.1038/s41467-023-40297-8 |
0.32 |
|
| 2022 |
Schneider P, Bekiaris PS, von Kamp A, Klamt S. StrainDesign: a Comprehensive Python Package for Computational Design of Metabolic Networks. Bioinformatics (Oxford, England). PMID 36111857 DOI: 10.1093/bioinformatics/btac632 |
0.325 |
|
| 2022 |
Klamt S, von Kamp A. Analyzing and Resolving Infeasibility in Flux Balance Analysis of Metabolic Networks. Metabolites. 12. PMID 35888712 DOI: 10.3390/metabo12070585 |
0.372 |
|
| 2021 |
Thiele S, von Kamp A, Bekiaris PS, Schneider P, Klamt S. CNApy: a CellNetAnalyzer GUI in Python for Analyzing and Designing Metabolic Networks. Bioinformatics (Oxford, England). PMID 34878104 DOI: 10.1093/bioinformatics/btab828 |
0.386 |
|
| 2020 |
Klamt S, Mahadevan R, von Kamp A. Speeding up the core algorithm for the dual calculation of minimal cut sets in large metabolic networks. Bmc Bioinformatics. 21: 510. PMID 33167871 DOI: 10.1186/s12859-020-03837-3 |
0.345 |
|
| 2020 |
Schneider P, von Kamp A, Klamt S. An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets. Plos Computational Biology. 16: e1008110. PMID 32716928 DOI: 10.1371/Journal.Pcbi.1008110 |
0.455 |
|
| 2020 |
Lieven C, Beber ME, Olivier BG, Bergmann FT, Ataman M, Babaei P, Bartell JA, Blank LM, Chauhan S, Correia K, Diener C, Dräger A, Ebert BE, Edirisinghe JN, Faria JP, ... ... Klamt S, et al. Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing. Nature Biotechnology. 38: 504. PMID 32265554 DOI: 10.1038/S41587-020-0477-4 |
0.362 |
|
| 2020 |
Lieven C, Beber ME, Olivier BG, Bergmann FT, Ataman M, Babaei P, Bartell JA, Blank LM, Chauhan S, Correia K, Diener C, Dräger A, Ebert BE, Edirisinghe JN, Faria JP, ... ... Klamt S, et al. MEMOTE for standardized genome-scale metabolic model testing. Nature Biotechnology. PMID 32123384 DOI: 10.1038/S41587-020-0446-Y |
0.368 |
|
| 2020 |
von Kamp A, Klamt S. MEMO: A Method for Computing Metabolic Modules for Cell-Free Production Systems. Acs Synthetic Biology. PMID 32069395 DOI: 10.1021/Acssynbio.9B00434 |
0.417 |
|
| 2020 |
Bekiaris PS, Klamt S. Automatic construction of metabolic models with enzyme constraints. Bmc Bioinformatics. 21: 19. PMID 31937255 DOI: 10.1186/S12859-019-3329-9 |
0.432 |
|
| 2019 |
Weinrich S, Koch S, Bonk F, Popp D, Benndorf D, Klamt S, Centler F. Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity. Frontiers in Microbiology. 10: 1095. PMID 31156601 DOI: 10.3389/Fmicb.2019.01095 |
0.437 |
|
| 2019 |
Boecker S, Zahoor A, Schramm T, Link H, Klamt S. Broadening the Scope of Enforced ATP Wasting as a Tool for Metabolic Engineering in Escherichia coli. Biotechnology Journal. e1800438. PMID 30927494 DOI: 10.1002/Biot.201800438 |
0.411 |
|
| 2019 |
Koch S, Kohrs F, Lahmann P, Bissinger T, Wendschuh S, Benndorf D, Reichl U, Klamt S. 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: e1006759. PMID 30707687 DOI: 10.1371/Journal.Pcbi.1006759 |
0.356 |
|
| 2019 |
Schneider P, Klamt S. Characterizing and Ranking Computed Metabolic Engineering Strategies. Bioinformatics (Oxford, England). PMID 30649194 DOI: 10.1093/Bioinformatics/Bty1065 |
0.394 |
|
| 2019 |
Klamt S, von Kamp A, Harder B. Computergestütztes Design mikrobieller Zellfabriken Biospektrum. 25: 156-158. DOI: 10.1007/S12268-019-1015-0 |
0.412 |
|
| 2018 |
Venayak N, von Kamp A, Klamt S, Mahadevan R. MoVE identifies metabolic valves to switch between phenotypic states. Nature Communications. 9: 5332. PMID 30552335 DOI: 10.1038/S41467-018-07719-4 |
0.483 |
|
| 2018 |
Hädicke O, von Kamp A, Aydogan T, Klamt S. 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: e1006492. PMID 30248096 DOI: 10.1371/Journal.Pcbi.1006492 |
0.797 |
|
| 2018 |
Mahour R, Klapproth J, Rexer TFT, Schildbach A, Klamt S, Pietzsch M, Rapp E, Reichl U. Establishment of a five-enzyme cell-free cascade for the synthesis of uridine diphosphate N-acetylglucosamine. Journal of Biotechnology. 283: 120-129. PMID 30044949 DOI: 10.1016/J.Jbiotec.2018.07.027 |
0.359 |
|
| 2018 |
Thiele S, Heise S, Hessenkemper W, Bongartz H, Fensky M, Schaper F, Klamt S. Designing optimal experiments to discriminate interaction graph models. Ieee/Acm Transactions On Computational Biology and Bioinformatics. PMID 29993657 DOI: 10.1109/Tcbb.2018.2812184 |
0.358 |
|
| 2018 |
Klamt S, Müller S, Regensburger G, Zanghellini J. A mathematical framework for yield (versus rate) optimization in constraint-based modeling and applications in metabolic engineering. Metabolic Engineering. PMID 29427605 DOI: 10.1016/J.Ymben.2018.02.001 |
0.426 |
|
| 2018 |
Klamt S. One-Stage vs. Two-Stage Bioprocesses: Comparative Computational and Experimental Studies and Consequences for Strain Design Ifac-Papersonline. 51: 7. DOI: 10.1016/J.Ifacol.2018.09.006 |
0.366 |
|
| 2017 |
Klamt S, Mahadevan R, Hädicke O. When do two-stage processes outperform one-stage processes? Biotechnology Journal. PMID 29131522 DOI: 10.1002/Biot.201700539 |
0.757 |
|
| 2017 |
Harder BJ, Bettenbrock K, Klamt S. Temperature-dependent dynamic control of the TCA cycle increases volumetric productivity of itaconic acid production by Escherichia coli. Biotechnology and Bioengineering. PMID 28865130 DOI: 10.1002/Bit.26446 |
0.325 |
|
| 2017 |
von Kamp A, Klamt S. Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms. Nature Communications. 8: 15956. PMID 28639622 DOI: 10.1038/Ncomms15956 |
0.444 |
|
| 2017 |
von Kamp A, Thiele S, Hädicke O, Klamt S. Use of CellNetAnalyzer in biotechnology and metabolic engineering. Journal of Biotechnology. 261: 221-228. PMID 28499817 DOI: 10.1016/J.Jbiotec.2017.05.001 |
0.805 |
|
| 2017 |
Klamt S, Regensburger G, Gerstl MP, Jungreuthmayer C, Schuster S, Mahadevan R, Zanghellini J, Müller S. From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints. Plos Computational Biology. 13: e1005409. PMID 28406903 DOI: 10.1371/Journal.Pcbi.1005409 |
0.492 |
|
| 2017 |
Hädicke O, Klamt S. Corrigendum: EColiCore2: a reference network model of the central metabolism of Escherichia coli and relationships to its genome-scale parent model. Scientific Reports. 7: 44520. PMID 28300137 DOI: 10.1038/Srep44520 |
0.778 |
|
| 2017 |
Hädicke O, Klamt S. EColiCore2: a reference network model of the central metabolism of Escherichia coli and relationships to its genome-scale parent model. Scientific Reports. 7: 39647. PMID 28045126 DOI: 10.1038/Srep39647 |
0.802 |
|
| 2016 |
Wu H, von Kamp A, Leoncikas V, Mori W, Sahin N, Gevorgyan A, Linley C, Grabowski M, Mannan AA, Stoy N, Stewart GR, Ward LT, Lewis DJM, Sroka J, Matsuno H, ... Klamt S, et al. MUFINS: multi-formalism interaction network simulator. Npj Systems Biology and Applications. 2: 16032. PMID 28725480 DOI: 10.1038/npjsba.2016.32 |
0.405 |
|
| 2016 |
Ud-Dean SM, Heise S, Klamt S, Gunawan R. TRaCE+: Ensemble inference of gene regulatory networks from transcriptional expression profiles of gene knock-out experiments. Bmc Bioinformatics. 17: 252. PMID 27342648 DOI: 10.1186/S12859-016-1137-Z |
0.323 |
|
| 2016 |
Harder BJ, Bettenbrock K, Klamt S. Model-Based Metabolic Engineering Enables High Yield Itaconic Acid Production by Escherichia coli. Metabolic Engineering. PMID 27269589 DOI: 10.1016/J.Ymben.2016.05.008 |
0.347 |
|
| 2016 |
Koch S, Benndorf D, Fronk K, Reichl U, Klamt S. Predicting compositions of microbial communities from stoichiometric models with applications for the biogas process. Biotechnology For Biofuels. 9: 17. PMID 26807149 DOI: 10.1186/S13068-016-0429-X |
0.324 |
|
| 2016 |
Gerstl MP, Klamt S, Jungreuthmayer C, Zanghellini J. Exact quantification of cellular robustness in genome-scale metabolic networks. Bioinformatics (Oxford, England). 32: 730-7. PMID 26543173 DOI: 10.1093/Bioinformatics/Btv649 |
0.495 |
|
| 2015 |
Hädicke O, Klamt S. Manipulation of the ATP pool as a tool for metabolic engineering. Biochemical Society Transactions. 43: 1140-5. PMID 26614651 DOI: 10.1042/Bst20150141 |
0.772 |
|
| 2015 |
Thiele S, Cerone L, Saez-Rodriguez J, Siegel A, Guziołowski C, Klamt S. Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies. Bmc Bioinformatics. 16: 345. PMID 26510976 DOI: 10.1186/S12859-015-0733-7 |
0.6 |
|
| 2015 |
Erdrich P, Steuer R, Klamt S. An algorithm for the reduction of genome-scale metabolic network models to meaningful core models. Bmc Systems Biology. 9: 48. PMID 26286864 DOI: 10.1186/S12918-015-0191-X |
0.487 |
|
| 2015 |
Klamt S, Mahadevan R. On the feasibility of growth-coupled product synthesis in microbial strains. Metabolic Engineering. 30: 166-78. PMID 26112955 DOI: 10.1016/J.Ymben.2015.05.006 |
0.456 |
|
| 2015 |
Mahadevan R, von Kamp A, Klamt S. Genome-scale strain designs based on regulatory minimal cut sets. Bioinformatics (Oxford, England). PMID 25913205 DOI: 10.1093/Bioinformatics/Btv217 |
0.353 |
|
| 2015 |
D'Alessandro LA, Samaga R, Maiwald T, Rho SH, Bonefas S, Raue A, Iwamoto N, Kienast A, Waldow K, Meyer R, Schilling M, Timmer J, Klamt S, Klingmüller U. Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling. Plos Computational Biology. 11: e1004192. PMID 25905717 DOI: 10.1371/Journal.Pcbi.1004192 |
0.421 |
|
| 2015 |
Hädicke O, Bettenbrock K, Klamt S. Enforced ATP futile cycling increases specific productivity and yield of anaerobic lactate production in Escherichia coli. Biotechnology and Bioengineering. 112: 2195-9. PMID 25899755 DOI: 10.1002/Bit.25623 |
0.762 |
|
| 2014 |
Erdrich P, Knoop H, Steuer R, Klamt S. Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling. Microbial Cell Factories. 13: 128. PMID 25323065 DOI: 10.1186/S12934-014-0128-X |
0.353 |
|
| 2014 |
Lohr V, Hädicke O, Genzel Y, Jordan I, Büntemeyer H, Klamt S, Reichl U. The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis. Bmc Biotechnology. 14: 72. PMID 25077436 DOI: 10.1186/1472-6750-14-72 |
0.731 |
|
| 2014 |
Ryll A, Bucher J, Bonin A, Bongard S, Gonçalves E, Saez-Rodriguez J, Niklas J, Klamt S. A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models. Bio Systems. 124: 26-38. PMID 25063553 DOI: 10.1016/J.Biosystems.2014.07.002 |
0.636 |
|
| 2014 |
von Kamp A, Klamt S. Enumeration of smallest intervention strategies in genome-scale metabolic networks. Plos Computational Biology. 10: e1003378. PMID 24391481 DOI: 10.1371/Journal.Pcbi.1003378 |
0.477 |
|
| 2014 |
Mueller C, Gupta N, Saalfeld FC, Findeisen R, Rudolph N, Klamt S, Heise S, Schaper F, Fischer T. Expression of JAK2-V617F Kinase in Myeloid Progenitors and Proerythroblasts Induces Differential Patterns of Hypersensitivity in Activation of Key Signaling Nodes upon Incubation with Low-Dose, Physiologic EPO Concentrations Blood. 124: 4573-4573. DOI: 10.1182/Blood.V124.21.4573.4573 |
0.301 |
|
| 2013 |
Chaouiya C, Bérenguier D, Keating SM, Naldi A, van Iersel MP, Rodriguez N, Dräger A, Büchel F, Cokelaer T, Kowal B, Wicks B, Gonçalves E, Dorier J, Page M, Monteiro PT, ... ... Klamt S, et al. SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools. Bmc Systems Biology. 7: 135. PMID 24321545 DOI: 10.1186/1752-0509-7-135 |
0.61 |
|
| 2013 |
Jungreuthmayer C, Nair G, Klamt S, Zanghellini J. Comparison and improvement of algorithms for computing minimal cut sets. Bmc Bioinformatics. 14: 318. PMID 24191903 DOI: 10.1186/1471-2105-14-318 |
0.302 |
|
| 2013 |
Gruchattka E, Hädicke O, Klamt S, Schütz V, Kayser O. In silico profiling of Escherichia coli and Saccharomyces cerevisiae as terpenoid factories. Microbial Cell Factories. 12: 84. PMID 24059635 DOI: 10.1186/1475-2859-12-84 |
0.772 |
|
| 2013 |
Melas IN, Samaga R, Alexopoulos LG, Klamt S. Detecting and removing inconsistencies between experimental data and signaling network topologies using integer linear programming on interaction graphs. Plos Computational Biology. 9: e1003204. PMID 24039561 DOI: 10.1371/Journal.Pcbi.1003204 |
0.399 |
|
| 2013 |
Pinna A, Heise S, Flassig RJ, de la Fuente A, Klamt S. Reconstruction of large-scale regulatory networks based on perturbation graphs and transitive reduction: improved methods and their evaluation. Bmc Systems Biology. 7: 73. PMID 23924435 DOI: 10.1186/1752-0509-7-73 |
0.385 |
|
| 2013 |
Samaga R, Klamt S. Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks. Cell Communication and Signaling : Ccs. 11: 43. PMID 23803171 DOI: 10.1186/1478-811X-11-43 |
0.45 |
|
| 2013 |
Hädicke O, Lohr V, Genzel Y, Reichl U, Klamt S. Evaluating differences of metabolic performances: statistical methods and their application to animal cell cultivations. Biotechnology and Bioengineering. 110: 2633-42. PMID 23568808 DOI: 10.1002/Bit.24926 |
0.775 |
|
| 2013 |
Gonçalves E, Bucher J, Ryll A, Niklas J, Mauch K, Klamt S, Rocha M, Saez-Rodriguez J. Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models. Molecular Biosystems. 9: 1576-83. PMID 23525368 DOI: 10.1039/C3Mb25489E |
0.61 |
|
| 2012 |
Flassig RJ, Heise S, Sundmacher K, Klamt S. An effective framework for reconstructing gene regulatory networks from genetical genomics data. Bioinformatics (Oxford, England). 29: 246-54. PMID 23175757 DOI: 10.1093/Bioinformatics/Bts679 |
0.345 |
|
| 2012 |
Huard J, Mueller S, Gilles ED, Klingmüller U, Klamt S. An integrative model links multiple inputs and signaling pathways to the onset of DNA synthesis in hepatocytes Febs Journal. 279: 3290-3313. PMID 22443451 DOI: 10.1111/J.1742-4658.2012.08572.X |
0.599 |
|
| 2012 |
Ballerstein K, von Kamp A, Klamt S, Haus UU. Minimal cut sets in a metabolic network are elementary modes in a dual network. Bioinformatics (Oxford, England). 28: 381-7. PMID 22190691 DOI: 10.1093/Bioinformatics/Btr674 |
0.462 |
|
| 2011 |
Ryll A, Samaga R, Schaper F, Alexopoulos LG, Klamt S. Large-scale network models of IL-1 and IL-6 signalling and their hepatocellular specification Molecular Biosystems. 7: 3253-3270. PMID 21968890 DOI: 10.1039/C1Mb05261F |
0.36 |
|
| 2011 |
Hädicke O, Grammel H, Klamt S. Metabolic network modeling of redox balancing and biohydrogen production in purple nonsulfur bacteria. Bmc Systems Biology. 5: 150. PMID 21943387 DOI: 10.1186/1752-0509-5-150 |
0.795 |
|
| 2011 |
Kaleta C, de Figueiredo LF, Heiland I, Klamt S, Schuster S. Special issue: integration of OMICs datasets into metabolic pathway analysis. Bio Systems. 105: 107-8. PMID 21619911 DOI: 10.1016/J.Biosystems.2011.05.008 |
0.414 |
|
| 2011 |
Klamt S, von Kamp A. An application programming interface for CellNetAnalyzer. Bio Systems. 105: 162-8. PMID 21315797 DOI: 10.1016/J.Biosystems.2011.02.002 |
0.433 |
|
| 2011 |
Hädicke O, Klamt S. Computing complex metabolic intervention strategies using constrained minimal cut sets. Metabolic Engineering. 13: 204-13. PMID 21147248 DOI: 10.1016/J.Ymben.2010.12.004 |
0.77 |
|
| 2010 |
Franke R, Theis FJ, Klamt S. From binary to multivalued to continuous models: the lac operon as a case study. Journal of Integrative Bioinformatics. 7. PMID 21200084 DOI: 10.2390/Biecoll-Jib-2010-151 |
0.395 |
|
| 2010 |
Klamt S, Flassig RJ, Sundmacher K. TRANSWESD: inferring cellular networks with transitive reduction. Bioinformatics (Oxford, England). 26: 2160-8. PMID 20605927 DOI: 10.1093/Bioinformatics/Btq342 |
0.349 |
|
| 2010 |
Hädicke O, Klamt S. CASOP: a computational approach for strain optimization aiming at high productivity. Journal of Biotechnology. 147: 88-101. PMID 20303369 DOI: 10.1016/J.Jbiotec.2010.03.006 |
0.786 |
|
| 2010 |
Samaga R, Von Kamp A, Klamt S. Computing combinatorial intervention strategies and failure modes in signaling networks. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 17: 39-53. PMID 20078396 DOI: 10.1089/Cmb.2009.0121 |
0.351 |
|
| 2009 |
Poltz R, Franke R, Schweitzer K, Klamt S, Gilles ED, Naumann M. Logical network of genotoxic stress-induced NF-κB signal transduction predicts putative target structures for therapeutic intervention strategies. Advances and Applications in Bioinformatics and Chemistry : Aabc. 2: 125-38. PMID 21918620 |
0.532 |
|
| 2009 |
Saez-Rodriguez J, Alexopoulos LG, Epperlein J, Samaga R, Lauffenburger DA, Klamt S, Sorger PK. Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction. Molecular Systems Biology. 5: 331. PMID 19953085 DOI: 10.1038/Msb.2009.87 |
0.611 |
|
| 2009 |
Wittmann DM, Krumsiek J, Saez-Rodriguez J, Lauffenburger DA, Klamt S, Theis FJ. Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling. Bmc Systems Biology. 3: 98. PMID 19785753 DOI: 10.1186/1752-0509-3-98 |
0.598 |
|
| 2009 |
Samaga R, Saez-Rodriguez J, Alexopoulos LG, Sorger PK, Klamt S. The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. Plos Computational Biology. 5: e1000438. PMID 19662154 DOI: 10.1371/Journal.Pcbi.1000438 |
0.607 |
|
| 2009 |
Klamt S, von Kamp A. Computing paths and cycles in biological interaction graphs. Bmc Bioinformatics. 10: 181. PMID 19527491 DOI: 10.1186/1471-2105-10-181 |
0.31 |
|
| 2008 |
Saez-Rodriguez J, Hammerle-Fickinger A, Dalal O, Klamt S, Gilles ED, Conradi C. Multistability of signal transduction motifs. Iet Systems Biology. 2: 80-93. PMID 18397119 DOI: 10.1049/Iet-Syb:20070012 |
0.667 |
|
| 2008 |
Haus UU, Klamt S, Stephen T. Computing knock-out strategies in metabolic networks. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 15: 259-68. PMID 18331197 DOI: 10.1089/Cmb.2007.0229 |
0.395 |
|
| 2008 |
Klamt S, Grammel H, Straube R, Ghosh R, Gilles ED. Modeling the electron transport chain of purple non-sulfur bacteria. Molecular Systems Biology. 4: 156. PMID 18197174 DOI: 10.1038/Msb4100191 |
0.571 |
|
| 2008 |
Franke R, Müller M, Wundrack N, Gilles ED, Klamt S, Kähne T, Naumann M. Host-pathogen systems biology: logical modelling of hepatocyte growth factor and Helicobacter pylori induced c-Met signal transduction. Bmc Systems Biology. 2: 4. PMID 18194572 DOI: 10.1186/1752-0509-2-4 |
0.562 |
|
| 2007 |
Saez-Rodriguez J, Simeoni L, Lindquist JA, Hemenway R, Bommhardt U, Arndt B, Haus UU, Weismantel R, Gilles ED, Klamt S, Schraven B. A logical model provides insights into T cell receptor signaling. Plos Computational Biology. 3: e163. PMID 17722974 DOI: 10.1371/Journal.Pcbi.0030163 |
0.703 |
|
| 2007 |
Beste DJ, Hooper T, Stewart G, Bonde B, Avignone-Rossa C, Bushell ME, Wheeler P, Klamt S, Kierzek AM, McFadden J. GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism. Genome Biology. 8: R89. PMID 17521419 DOI: 10.1186/Gb-2007-8-5-R89 |
0.386 |
|
| 2007 |
Klamt S, Saez-Rodriguez J, Gilles ED. Structural and functional analysis of cellular networks with CellNetAnalyzer. Bmc Systems Biology. 1: 2. PMID 17408509 DOI: 10.1186/1752-0509-1-2 |
0.723 |
|
| 2006 |
Saez-Rodriguez J, Mirschel S, Hemenway R, Klamt S, Gilles ED, Ginkel M. Visual setup of logical models of signaling and regulatory networks with ProMoT. Bmc Bioinformatics. 7: 506. PMID 17109765 DOI: 10.1186/1471-2105-7-506 |
0.721 |
|
| 2006 |
Klamt S, Saez-Rodriguez J, Lindquist JA, Simeoni L, Gilles ED. A methodology for the structural and functional analysis of signaling and regulatory networks. Bmc Bioinformatics. 7: 56. PMID 16464248 DOI: 10.1186/1471-2105-7-56 |
0.718 |
|
| 2006 |
Klamt S. Generalized concept of minimal cut sets in biochemical networks. Bio Systems. 83: 233-47. PMID 16303240 DOI: 10.1016/J.Biosystems.2005.04.009 |
0.396 |
|
| 2004 |
Gagneur J, Klamt S. Computation of elementary modes: a unifying framework and the new binary approach. Bmc Bioinformatics. 5: 175. PMID 15527509 DOI: 10.1186/1471-2105-5-175 |
0.417 |
|
| 2004 |
Papin JA, Stelling J, Price ND, Klamt S, Schuster S, Palsson BO. Comparison of network-based pathway analysis methods. Trends in Biotechnology. 22: 400-5. PMID 15283984 DOI: 10.1016/J.Tibtech.2004.06.010 |
0.485 |
|
| 2004 |
Klamt S, Gilles ED. Minimal cut sets in biochemical reaction networks. Bioinformatics (Oxford, England). 20: 226-34. PMID 14734314 DOI: 10.1093/Bioinformatics/Btg395 |
0.678 |
|
| 2004 |
Kremling A, Klamt S, Ginkel M, Gilles E. Workbench zur Modellbildung, Simulation und Analyse zellulärer Systeme (Workbench for Model Set Up, Simulation, and Analysis of Cellular Systems) It - Information Technology. 46. DOI: 10.1524/Itit.46.1.12.26503 |
0.608 |
|
| 2003 |
Klamt S, Stelling J. Two approaches for metabolic pathway analysis? Trends in Biotechnology. 21: 64-9. PMID 12573854 DOI: 10.1016/S0167-7799(02)00034-3 |
0.487 |
|
| 2003 |
Klamt S, Stelling J, Ginkel M, Gilles ED. FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics (Oxford, England). 19: 261-9. PMID 12538248 DOI: 10.1093/Bioinformatics/19.2.261 |
0.687 |
|
| 2002 |
Stelling J, Klamt S, Bettenbrock K, Schuster S, Gilles ED. Metabolic network structure determines key aspects of functionality and regulation Nature. 420: 190-193. PMID 12432396 DOI: 10.1038/Nature01166 |
0.684 |
|
| 2002 |
Klamt S, Schuster S. Calculating as many fluxes as possible in underdetermined metabolic networks. Molecular Biology Reports. 29: 243-8. PMID 12241065 DOI: 10.1023/A:1020394300385 |
0.401 |
|
| 2002 |
Klamt S, Stelling J. Combinatorial complexity of pathway analysis in metabolic networks. Molecular Biology Reports. 29: 233-6. PMID 12241063 DOI: 10.1023/A:1020390132244 |
0.476 |
|
| 2002 |
Klamt S, Schuster S, Gilles ED. Calculability analysis in underdetermined metabolic networks illustrated by a model of the central metabolism in purple nonsulfur bacteria Biotechnology and Bioengineering. 77: 734-751. PMID 11835134 DOI: 10.1002/Bit.10153 |
0.684 |
|
| 2002 |
Schuster S, Klamt S. Applying metabolic pathway analysis to make good use of methanol Trends in Biotechnology. 20: 322. DOI: 10.1016/S0167-7799(02)02026-7 |
0.501 |
|
| 2002 |
Schuster S, Klamt S. Applying metabolic pathway analysis to make good use of methanol Trends in Biotechnology. 20: 322. DOI: 10.1016/S0167-7799(02)02026-7 |
0.309 |
|
| 2001 |
Klamt S, Kremling A, Gilles E. Fluxanalyzer : A Graphical Interface for Stoichiometric and Quantitative Analysis of Metabolic Networks Ifac Proceedings Volumes. 34: 119-124. DOI: 10.1016/S1474-6670(17)34206-4 |
0.723 |
|
| 2001 |
Schuster S, Klamt S, Weckwerth W, Moldenhauer F, Pfeiffer T. Use of network analysis of metabolic systems in bioengineering Bioprocess and Biosystems Engineering. 24: 363-372. DOI: 10.1007/S004490100253 |
0.489 |
|
| Show low-probability matches. |