World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
13353
World Ranking
6346
National Ranking
297

Sebastian Böcker publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Sebastian Böcker sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 145 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Sebastian Böcker D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Sebastian Böcker sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Sebastian Böcker is affiliated with Friedrich Schiller University Jena in Germany, contributing extensively to the fields of biochemistry, genetics, and molecular biology, as well as chemistry. Their research primarily focuses on metabolomics and mass spectrometry studies, with significant work in analytical chemistry and chromatography, advanced chemical sensor technologies, and computational drug discovery methods.

Their recent publications include the following papers:

  • Feature-based molecular networking in the GNPS analysis environment, 2020, Nature Methods
  • Integrative analysis of multimodal mass spectrometry data in MZmine 3, 2023, Nature Biotechnology
  • Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra, 2020, Nature Biotechnology
  • Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment, 2021, Nature Communications
  • High-confidence structural annotation of metabolites absent from spectral libraries, 2021, Nature Biotechnology

Böcker frequently collaborates with several researchers, including Kai Dührkop, Pieter C. Dorrestein, Marcus Ludwig, Louis-Félix Nothias, and Daniel Petras. These collaborations have contributed to their research output significantly.

The scientist has published in various venues, with multiple publications appearing in bioRxiv (Cold Spring Harbor Laboratory), Nature Communications, Nature Methods, Nature Biotechnology, and Nature Machine Intelligence.

Their main fields of study encompass:

  • Biochemistry, Genetics and Molecular Biology
  • Chemistry

Within these broader fields, Böcker's subfields of study include:

  • Molecular Biology
  • Spectroscopy
  • Biomedical Engineering
  • Computational Theory and Mathematics
  • Ecology

Key topics covered in their work are:

  • Metabolomics and Mass Spectrometry Studies
  • Analytical Chemistry and Chromatography
  • Advanced Chemical Sensor Technologies
  • Mass Spectrometry Techniques and Applications
  • Computational Drug Discovery Methods
  • Isotope Analysis in Ecology
  • Genomics and Phylogenetic Studies

Best Publications

  • SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information.

    Kai Dührkop;Markus Fleischauer;Marcus Ludwig;Alexander A. Aksenov

  • Feature-based molecular networking in the GNPS analysis environment.

    Louis-Félix Nothias;Louis-Félix Nothias;Daniel Petras;Daniel Petras;Robin Schmid;Kai Dührkop

  • Searching molecular structure databases with tandem mass spectra using CSI:FingerID.

    Kai Dührkop;Huibin Shen;Marvin Meusel;Juho Rousu

  • Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra

    Kai Dührkop;Louis Felix Nothias;Markus Fleischauer;Raphael Reher

  • SIRIUS: decomposing isotope patterns for metabolite identification

    Sebastian Böcker;Matthias C. Letzel;Zsuzsanna Lipták;Anton Pervukhin

  • Exact Algorithms for Cluster Editing: Evaluation and Experiments

    Sebastian Böcker;Sebastian Briesemeister;Gunnar W. Klau

  • High-confidence structural annotation of metabolites absent from spectral libraries.

    Martin A. Hoffmann;Martin A. Hoffmann;Louis-Félix Nothias;Louis-Félix Nothias;Marcus Ludwig;Markus Fleischauer

  • Fragmentation trees reloaded

    Sebastian Böcker;Kai Dührkop

  • Computational mass spectrometry for metabolomics: Identification of metabolites and small molecules

    Steffen Neumann;Sebastian Böcker

  • Critical Assessment of Small Molecule Identification 2016: automated methods

    Emma L. Schymanski;Christoph Ruttkies;Martin Krauss;Céline Brouard;Céline Brouard

  • Database-independent molecular formula annotation using Gibbs sampling through ZODIAC

    Marcus Ludwig;Louis-Félix Nothias;Kai Dührkop;Irina Koester;Irina Koester

  • Significance estimation for large scale metabolomics annotations by spectral matching

    Kerstin Scheubert;Franziska Hufsky;Daniel Petras;Mingxun Wang

  • High-throughput MALDI-TOF discovery of genomic sequence polymorphisms.

    Patrick Stanssens;Marc Zabeau;Geert Meersseman;Gwen Remes

  • Computational mass spectrometry for small molecules

    Kerstin Scheubert;Franziska Hufsky;Franziska Hufsky;Sebastian Böcker

  • Towards de novo identification of metabolites by analyzing tandem mass spectra

    Sebastian Böcker;Florian Rasche

  • Partitioning biological data with transitivity clustering.

    Tobias Wittkop;Tobias Wittkop;Tobias Wittkop;Dorothea Emig;Sita J. Lange;Sven Rahmann

  • Simple but fundamental limitations on supertree and consensus tree methods.

    Mike Steel;Andreas W. M. Dress;Sebastian Böcker

  • Metabolite identification through multiple kernel learning on fragmentation trees.

    Huibin Shen;Kai Dührkop;Sebastian Böcker;Juho Rousu

  • Going weighted: Parameterized algorithms for cluster editing

    S. Böcker;S. Briesemeister;Q. B. A. Bui;A. Truss

  • Computational mass spectrometry for small-molecule fragmentation

    Franziska Hufsky;Franziska Hufsky;Kerstin Scheubert;Sebastian Böcker

  • Feature-based Molecular Networking in the GNPS Analysis Environment

    Louis Felix Nothias;Daniel Petras;Robin Schmid;Kai Dührkop

  • Fragmentation Trees Reloaded

    Kai Dührkop;Sebastian Böcker

Frequent Co-Authors

Pieter C. Dorrestein
Pieter C. Dorrestein University of California, San Diego
Daniel Petras
Daniel Petras University of California, Riverside
Aleš Svatoš
Aleš Svatoš Max Planck Society
Juho Rousu
Juho Rousu Aalto University
Jens Stoye
Jens Stoye Bielefeld University
Justin J. J. van der Hooft
Justin J. J. van der Hooft Wageningen University & Research
Steffen Neumann
Steffen Neumann Leibniz Institute of Plant Biochemistry
Gunnar W. Klau
Gunnar W. Klau Heinrich Heine University Düsseldorf
Andreas W. M. Dress
Andreas W. M. Dress Max Planck Institute for Mathematics in the Sciences
Ulrich S. Schubert
Ulrich S. Schubert Friedrich Schiller University Jena

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