Publications 2001 - now

[57] Beck C, Knoop H, Steuer R (2018) [https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1007239|Modules of co-occurrence in the cyanobacterial pan-genome reveal functional associations between groups of ortholog genes.]] PLoS Genet 14(3): e1007239. https://doi.org/10.1371/journal.pgen.1007239

[56] Faizi M, Zavrel T, Loureiro C, Cerveny J, Steuer R (2018) [https://www.ncbi.nlm.nih.gov/pubmed/29476802|A model of optimal protein allocation during phototrophic growth.]] Biosystems. pii: S0303-2647(18)30009-1. doi: 10.1016/j.biosystems.2018.02.004.

[55] Lippi L, Bähr L, Wüstenberg A, Wilde A, Steuer R​ (2018) Exploring the potential of high-density cultivation of cyanobacteria for the production of cyanophycin. Algal Research 31, 363–366. https://doi.org/10.1016/j.algal.2018.02.028

[54] Reimers AM, Knoop H, Bockmayr A, Steuer R.​ (2017) Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth. Proc Natl Acad Sci U S A. pii: 201617508. doi: 10.1073/pnas.1617508114.

[53] Marianne Gründel, Henning Knoop​, Ralf Steuer​ (2017) Activity and functional properties of the isocitrate lyase in the cyanobacterium Cyanothece sp. PCC 7424 Microbiology. doi: 10.1099/mic.0.000459

[52] Malatinszky D, Steuer R, Jones PR. (2017) A comprehensively curated genome-scale two-cell model for the cyanobacterium Anabaena sp. PCC 7120. Plant Physiol. 173(1):509-523. doi: 10.1104/pp.16.01487

[51] Westermark S and Steuer R (2016) Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach. Front. Bioeng. Biotechnol. 4:95. doi: 10.3389/fbioe.2016.00095

[50] Baum K, Politi AZ, Kofahl B, Steuer R, Wolf J. (2016) Feedback, Mass Conservation and Reaction Kinetics Impact the Robustness of Cellular Oscillations. PLoS Comput Biol. 2016 Dec 27;12(12):e1005298

[49] Zavřel T, Červený J, Knoop H, Steuer R (2016) Optimizing cyanobacterial product synthesis: Meeting the challenges. Bioengineered. 2016 Jul 15:1-7.

[48] Zavřel T, Knoop H, Steuer R, Jones PR, Červený J, Trtílek M. (2016) A quantitative evaluation of ethylene production in the recombinant cyanobacterium Synechocystis sp. PCC 6803 harboring the ethylene-forming enzyme by membrane inlet mass spectrometry. Bioresour Technol. 202:142-51. doi: 10.1016/j.biortech.2015.11.062.

[47] Muller S, Regensburger G, Steuer R. (2015) Resource allocation in metabolic networks: kinetic optimization and approximations by FBA. Biochem Soc Trans. 2015 Dec 1;43(6):1195-200. doi: 10.1042/BST20150156. Review.

[46] Ruegen M, Bockmayr A, Steuer R. (2015) Elucidating temporal resource allocation and diurnal dynamics in phototrophic metabolism using conditional FBA Sci Rep. 2015 Oct 26;5:15247. doi: 10.1038/srep15247.

[45] Erdrich P, Steuer R, Klamt S. (2015) An algorithm for the reduction of genome-scale metabolic network models to meaningful core models. BMC Syst Biol. 2015 Aug 19;9:48. doi: 10.1186/s12918-015-0191-x.

[44] Knoop H, Steuer R. (2015) A computational analysis of stoichiometric constraints and trade-offs in cyanobacterial biofuel production. Front Bioeng Biotechnol. 3:47. doi: 10.3389/fbioe.2015.00047.

[43] Klemke F, Baier A, Knoop H, Kern R, Jablonsky J, Beyer G, Volkmer T, Steuer R, Lockau W, Hagemann M. (2015) Identification of the light-independent phosphoserine pathway as additional source for serine in the cyanobacterium Synechocystis sp. PCC 6803. Microbiology. 2015 Feb 20. pii: mic.0.000055. doi: 10.1099/mic.0.000055.

[42] Murabito E, Verma M, Bekker M, Bellomo D, Westerhoff HV, Teusink B, Steuer R. (2014) Monte-Carlo modeling of the central carbon metabolism of Lactococcus lactis: insights into metabolic regulation. PLoS One. 9(9):e106453.

[41] Erdrich P, Knoop H, Steuer R, Klamt S. (2014) Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling. Microb Cell Fact. 2014 Sep 19;13(1):128.

[40] Müller S, Regensburger G, Steuer R. (2014) Enzyme allocation problems in kinetic metabolic networks: Optimal solutions are elementary flux modes. J Theor Biol. 347:182-90. doi: 10.1016/j.jtbi.2013.11.015.

[39] Gottstein W, Müller S, Herzel H, Steuer R. (2014) Elucidating the adaptation and temporal coordination of metabolic pathways using in-silico evolution. Biosystems. 117:68-76. doi: 10.1016/j.biosystems.2013.12.006.

[38] Klement M, Děd T, Šafránek D, Červený J, Müller S, Steuer R. (2014) Biochemical Space: A Framework for Systemic Annotation of Biological Models. Electronic Notes in Theoretical Computer Science, Volume 306, 2014, Pages 31-44, ISSN 1571-0661, https://doi.org/10.1016/j.entcs.2014.06.013.

[37] H. Knoop, M. Gruendel, Y. Zilliges, R. Lehmann, S. Hoffmann, W. Lockau, R. Steuer. (2013) Flux Balance Analysis of Cyanobacterial Metabolism: The metabolic network of Synechocystis sp. PCC 6803. PLoS Comput Biol 9(6): e1003081. doi:10.1371/journal.pcbi.1003081

[36] R. Lehmann, R. Machne, J. Georg , M. Benary, I. M. Axmann, R. Steuer (2013) How cyanobacteria pose new problems to old methods: Challenges in microarray time series analysis. BMC Bioinformatics 14:133. doi: 10.1186/1471-2105-14-133.

[35] Klement M, Šafránek D, Děd T, Pejznoch A, Nedbal L, Steuer R, Červený J, Müller S (2013) A Comprehensive Web-based Platform For Domain-Specific Biological Models. Electronic Notes in Theoretical Computer Science, Volume 299, 2013, Pages 61-67, ISSN 1571-0661, https://doi.org/10.1016/j.entcs.2013.11.006.

[34] Kämäräinen J, Knoop H, Stanford NJ, Guerrero F, Akhtar MK, Aro EM, Steuer R, Jones PR. (2012) Physiological tolerance and stoichiometric potential of cyanobacteria for hydrocarbon fuel production. J Biotechnol. 162(1):67-74. doi: 10.1016/j.jbiotec.2012.07.193.

[33] R. Steuer, H. Knoop, R. Machne (2012) Modelling cyanobacteria: from metabolism to integrative models of phototrophic growth. Journal of Experimental Botany 63(6):2259-74. doi:10.1093/jxb/ers018

[32] C. Beck, H. Knoop, IM Axmann, R. Steuer (2012) The diversity of cyanobacterial metabolism: genome analysis of multiple phototrophic microorganisms. BMC Genomics. 13(1):56.

[31] Steuer R, Waldherr S, Sourjik V, Kollmann M (2011) Robust Signal Processing in Living Cells. PLoS Comput Biol 7(11): e1002218. doi:10.1371/journal.pcbi.1002218

[30] E. Murabito, K. Smallbone, J. Swinton, H. V. Westerhoff, R. Steuer (2011) A probabilistic approach to identify putative drug targets in biochemical networks. J R Soc Interface. 8(59):880-95.

[29] R. Steuer (2011) Exploring the Dynamics of Large-Scale Biochemical Networks: A Computational Perspective. The Open Bioinformatics Journal Vol. 5, pp.4-15

[28] H. Koeppl, S. Andreozzi, and R. Steuer (2011) Guaranteed and Randomized Methods for Stability Analysis of Uncertain Metabolic Networks. Lecture Notes in Control and Information Sciences, Volume 407, 297-307

[27] H. Knoop, Y. Zilliges, W. Lockau and R. Steuer (2010) The metabolic network of Synechocystis sp. PCC 6803: Systemic properties of autotrophic growth. Plant Physiol. 154(1):410-22.

[26] P. D. Kourdis, Ralf Steuer, and D. A. Goussis (2010) Physical understanding of complex multiscale biochemical models via algorithmic simplification: Glycolysis in Saccharomyces cerevisiae. Physica D Vol. 239, Issue 18, pp. 1798-1817

[25] R. Steuer and B. H. Junker (2009) Computational Models of Metabolism: Stability and Regulation in Metabolic Networks. Advances in Chemical Physics, Volume 142. Rice, Stuart A. (editor), ISBN-10: 0-470-46499-2 ISBN-13: 978-0-470-46499-1 - John Wiley & Sons (2009)

[24] SV Albers, NK Birkeland, AJ Driessen et al. (2009) SulfoSYS (Sulfolobus Systems Biology): towards a silicon cell model for the central carbohydrate metabolism of the archaeon Sulfolobus solfataricus under temperature variation. Biochem Soc Trans. 37(Pt 1):58-64

[23] J. Schmiedel and R. Steuer (2008) From minimal to full-scale models of yeast glycolysis: The role of feedback mechanisms in maintaining stability. in: Proceedings of the 5th Workshop on Computation of Biochemical Pathways and Genetic Networks, Heidelberg 22-23, 2008. R. Gauges, U. Kummer, J. Pahle and P. Willy (editors). Logos Verlag Berlin. ISBN 978-3-8325-1993-3.

[22] R. Steuer and G. Zamora-Lopez (2008) Global Properties of Networks (Review) , in: Junker BH and Schreiber F (eds.). Analysis of Biological Networks. Wiley Series on Bioinformatics: Computational Techniques and Engineering. Print ISBN: 9780470041444, Online ISBN: 9780470253489 (2008).

[21] D. Stiefs, T. Gross, R. Steuer, U. Feudel (2008) Computation and Visualization of Bifurcation Surfaces Intern. J. of Bifurcation and Chaos (IJBC), Vol. 18, No. 8, pp. 2191-2206

[20] Grimbs S, Selbig J, Bulik S, Holzhütter HG, and Steuer R (2007) The stability and robustness of metabolic states: identifying stabilizing sites in metabolic networks Molecular Systems Biology 3 Article number: 146 doi:10.1038/msb4100186

[19] Steuer R. (2007) Computational approaches to the topology, stability and dynamics of metabolic networks. Phytochemistry 68(16-18):2139-51, doi:10.1016/j.phytochem.2007.04.041

[18] Steuer R, Nunes Nesi A, Fernie AR, Gross T, Blasius B, Selbig J. (2007) From Structure to Dynamics of Metabolic Pathways: Application to the Plant Mitochondrial TCA Cycle. Bioinformatics 23(11):1378-85, doi:10.1093/bioinformatics/btm065

[17] Steuer R, Morgenthal K, Weckwerth W, Selbig J. (2007) A gentle guide to the analysis of metabolomic data. Methods Mol Biol. 358:105-26.

[16] Steuer R, Gross T, Selbig J, Blasius B. (2006) Structural kinetic modeling of metabolic networks Proc Natl Acad Sci U S A. 103(32):11868-73.

[15] Morgenthal K., Weckwerth W., Steuer R. (2006) Metabolomic networks in plants: Transitions from pattern recognition to biological interpretation. Biosystems. 83(2-3):108-17.

[14] Steuer R, Humburg P, Selbig J. (2006) Validation and functional annotation of expression-based clusters based on gene ontology. BMC Bioinformatics. 15;7:380.

[13] Steuer, R. (2006) On the analysis and interpretation of correlations in metabolomic data. Brief Bioinform. 7(2):151-8.

[12] W. Weckwerth and R. Steuer (2005) From Experiment to Biological Interpretation: Metabolic Networks from a Systems Perspective In: Metabolome Analyses: Strategies for Systems Biology. S. Vaidyanathan (Editor), G. G. Harrigan (Editor), R. Goodacre (Editor). Chapter 15, pp. 265-290. Springer; 1 edition

[11] Ralf Steuer (2004) Effects of stochasticity in models of the cell cycle: From quantized cycle times to noise-induced oscillations. J Theor Biol. 228(3):293-301.

[10] C. O. Daub, R. Steuer. S. Kloska, J. Selbig (2004) Improving estimates of mutual information using B-spline functions. BMC Bioinformatics. 5: 118, doi: 10.1186/1471-2105-5-118.

[9] R. Steuer, C. O. Daub, J. Selbig and J. Kurths (2004) Measuring Distances between Variables by Mutual Information. in: Proceedings of the 27th annual conference of the Gfkl, D. Baier and K.-D. Wernecke (eds) ,Springer-Verlag

[8] R. Steuer, W. Ebeling, T. Bengner, C. Dehnicke, H. Haettig and H.-J. Meencke (2004) Entropy and complexity analysis of intracranially recorded EEG. International Journal of Bifurcation and Chaos, Vol. 14, No. 2, pp. 815-823

[7] R. Steuer, J. Kurths, O. Fiehn and W. Weckwerth (2003) Observing and interpreting correlations in metabolomic networks. Bioinformatics, Vol. 19 (8), 1019-1026

[6] R. Steuer and C. Zhou and J. Kurths (2003) Constructive effects of fluctuations in genetic and biochemical regulatory systems. BioSystems, Vol. 72, 241-251

[5] R. Steuer, J. Kurths, O. Fiehn and W. Weckwerth (2003) Interpreting correlations in metabolomic networks. Biochemical Society Transactions, Vol. 31 (6), 1476-1478

[4] R. Steuer, J. Kurths, C. O. Daub, J. Weise and J. Selbig (2002) The Mutual Information: Detecting and evaluating dependencies between variables. Bioinformatics, Vol. 18 (Suppl. 2), S231-S240

[3] R. Steuer, W. Ebeling, D. F. Russell, S. Bahar, A. Neiman and F. Moss (2001) Entropy and local uncertainty of data from sensory neurons. Phys. Rev. E 64, 061911

[2] W. Ebeling, R. Steuer and M. R. Titchener (2001) Partition-based entropies of deterministic and stochastic maps. Stochastics and Dynamics, Vol. 1 (1), 45-61

[1] R. Steuer, L. Molgedey, W. Ebeling and M. A. Jimenez-Montano (2001) Entropy and optimal partition for data analysis. Eur. Phys. J. B 19, 265-269