World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
12439
World Ranking
3789
National Ranking
117

Steffen Klamt publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Steffen Klamt sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 135 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Steffen Klamt D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Steffen Klamt sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 51 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Steffen Klamt is affiliated with the Max Planck Institute for Dynamics of Complex Technical Systems in Germany. Their research spans multiple fields including Biochemistry, Genetics and Molecular Biology, and Engineering.

Their subfields of study include Molecular Biology, Biomedical Engineering, Control and Systems Engineering, Environmental Engineering, and Genetics. The main topics covered in their work involve Microbial Metabolic Engineering and Bioproduction, Biofuel production and bioconversion, Enzyme Catalysis and Immobilization, Gene Regulatory Network Analysis, Viral Infectious Diseases and Gene Expression in Insects, Process Optimization and Integration, and ATP Synthase and ATPases Research.

Steffen Klamt has published extensively, with notable recent papers including:

  • MEMOTE for standardized genome-scale metabolic model testing, 2020, Nature Biotechnology
  • SBML Level 3: an extensible format for the exchange and reuse of biological models, 2020, Molecular Systems Biology
  • Automatic construction of metabolic models with enzyme constraints, 2020, BMC Bioinformatics
  • An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets, 2020, PLoS Computational Biology
  • Blending industrial blast furnace gas with H2 enables Acetobacterium woodii to efficiently co-utilize CO, CO2 and H2, 2020, Bioresource Technology

The frequent coauthors working with Steffen Klamt are:

  • Katja Bettenbrock
  • Sebastián Espinel-Ríos
  • Rolf Findeisen
  • Simon Boecker
  • Axel von Kamp

Steffen Klamt has a record of publications in various venues, with the most frequent publication outlets being:

  • IFAC-PapersOnLine
  • Microbial Cell Factories
  • Metabolic Engineering
  • Bioinformatics
  • Nature Biotechnology

Best Publications

  • Metabolic network structure determines key aspects of functionality and regulation

    Jörg Stelling;Steffen Klamt;Katja Bettenbrock;Stefan Schuster

  • Structural and functional analysis of cellular networks with CellNetAnalyzer

    Steffen Klamt;Julio Saez-Rodriguez;Ernst Dieter Gilles

  • Hypergraphs and cellular networks.

    Steffen Klamt;Utz-Uwe Haus;Fabian J. Theis

  • MEMOTE for standardized genome-scale metabolic model testing

    Christian Lieven;Moritz Emanuel Beber;Brett G. Olivier;Frank T. Bergmann

  • A methodology for the structural and functional analysis of signaling and regulatory networks

    Steffen Klamt;Julio Saez-Rodriguez;Jonathan A. Lindquist;Luca Simeoni

  • Comparison of network-based pathway analysis methods

    Jason A. Papin;Joerg Stelling;Nathan D. Price;Steffen Klamt

  • A Logical Model Provides Insights into T Cell Receptor Signaling

    Julio Saez-Rodriguez;Luca Simeoni;Jonathan A. Lindquist;Rebecca Hemenway

  • Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction

    Julio Saez-Rodriguez;Julio Saez-Rodriguez;Leonidas G Alexopoulos;Leonidas G Alexopoulos;Jonathan Epperlein;Regina Samaga

  • Two approaches for metabolic pathway analysis

    Steffen Klamt;Jörg Stelling

  • Minimal cut sets in biochemical reaction networks

    Steffen Klamt;Ernst Dieter Gilles

  • Computation of elementary modes : a unifying framework and the new binary approach

    Julien Gagneur;Steffen Klamt

  • Combinatorial complexity of pathway analysis in metabolic networks.

    Steffen Klamt;Jörg Stelling

  • Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling

    Dominik M Wittmann;Jan Krumsiek;Julio Saez-Rodriguez;Julio Saez-Rodriguez;Douglas A Lauffenburger

  • FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps.

    Steffen Klamt;Jörg Stelling;Martin Ginkel;Ernst Dieter Gilles

  • SBML Level 3: an extensible format for the exchange and reuse of biological models

    Sarah M. Keating;Sarah M. Keating;Dagmar Waltemath;Matthias König;Fengkai Zhang

  • GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism

    Dany J V Beste;Tracy Hooper;Graham Stewart;Bhushan Bonde

  • The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data

    Regina Samaga;Julio Saez-Rodriguez;Leonidas G. Alexopoulos;Leonidas G. Alexopoulos;Leonidas G. Alexopoulos;Peter Karl Sorger;Peter Karl Sorger

  • SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

    Claudine Chaouiya;Duncan Bérenguier;Sarah M. Keating;Aurélien Naldi

  • Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms.

    Axel von Kamp;Steffen Klamt

  • Model-Based metabolic engineering enables high yield itaconic acid production by Escherichia coli

    Björn-Johannes Harder;Katja Bettenbrock;Steffen Klamt

Frequent Co-Authors

Udo Reichl
Udo Reichl Otto-von-Guericke University Magdeburg
Julio Saez-Rodriguez
Julio Saez-Rodriguez Heidelberg University
Stefan Schuster
Stefan Schuster Friedrich Schiller University Jena
Radhakrishnan Mahadevan
Radhakrishnan Mahadevan University of Toronto
Ernst Dieter Gilles
Ernst Dieter Gilles Max Planck Society
Kai Sundmacher
Kai Sundmacher Max Planck Institute for Dynamics of Complex Technical Systems
Bernhard O. Palsson
Bernhard O. Palsson University of California, San Diego
Jens Nielsen
Jens Nielsen Chalmers University of Technology
Sang Yup Lee
Sang Yup Lee Korea Advanced Institute of Science and Technology
Hans V. Westerhoff
Hans V. Westerhoff Vrije Universiteit Amsterdam

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