World's Best Scientists 2026 revealed!

D-Index & Metrics

Chemistry

D-Index
46
Citations
17656
World Ranking
15834
National Ranking
3960

Tobias Kind publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Tobias Kind sits on this spectrum.

61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61 publications 1,295+

This scientist: 121 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,295 publications or more.

Tobias Kind D-index placement in Chemistry in 2026

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

40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40 D-Index 159+

This scientist: 46 D-Index — 12th percentile

12% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

Overview

Tobias Kind is affiliated with the University of California, Davis in the United States. Their research primarily focuses on the fields of chemistry and biochemistry, genetics, and molecular biology, with a significant volume of work related to metabolomics and mass spectrometry studies.

Their published work covers a range of topics in analytical chemistry, chromatography, mass spectrometry techniques, and computational drug discovery methods. The scientist's research spans subfields including spectroscopy, molecular biology, computational theory and mathematics, radiation, and physical and theoretical chemistry.

Recent papers authored or co-authored by Tobias Kind include:

  • "Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics," 2020, Analytical Chemistry
  • "Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification," 2021, Nature Methods
  • "Quantum Chemistry Calculations for Metabolomics," 2021, Chemical Reviews
  • "Age and sex are associated with the plasma lipidome: findings from the GOLDN study," 2021, Lipids in Health and Disease
  • "Predicting in silico electron ionization mass spectra using quantum chemistry," 2020, Journal of Cheminformatics

The scientist has collaborated frequently with several co-authors, including Oliver Fiehn, Dean J. Tantillo, Shunyang Wang, Marguerite R. Irvin, and Dinesh Kumar Barupal.

Notable venues for Tobias Kind's publications include Zenodo (CERN European Organization for Nuclear Research), Analytical Chemistry, bioRxiv (Cold Spring Harbor Laboratory), Lipids in Health and Disease, and the Journal of Cheminformatics.

The research topics covered extensively in their publications are:

  • Metabolomics and Mass Spectrometry Studies
  • Analytical Chemistry and Chromatography
  • Mass Spectrometry Techniques and Applications
  • Computational Drug Discovery Methods
  • Ion-surface interactions and analysis
  • X-ray Spectroscopy and Fluorescence Analysis
  • Various Chemistry Research Topics

Best Publications

  • MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis.

    Hiroshi Tsugawa;Tomas Cajka;Tobias Kind;Yan Ma

  • FiehnLib: Mass Spectral and Retention Index Libraries for Metabolomics Based on Quadrupole and Time-of-Flight Gas Chromatography/Mass Spectrometry

    Tobias Kind;Gert Wohlgemuth;Do Yup Lee;Yun Lu

  • Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

    Tobias Kind;Oliver Fiehn

  • LipidBlast in silico tandem mass spectrometry database for lipid identification

    Tobias Kind;Kwang Hyeon Liu;Kwang Hyeon Liu;Do Yup Lee;Do Yup Lee;Brian Defelice

  • Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm

    Tobias Kind;Oliver Fiehn

  • Quality control for plant metabolomics: reporting MSI‐compliant studies

    Oliver Fiehn;Gert Wohlgemuth;Martin Scholz;Tobias Kind

  • Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics.

    Ivana Blaženović;Tobias Kind;Jian Ji;Oliver Fiehn;Oliver Fiehn

  • Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software

    Hiroshi Tsugawa;Tobias Kind;Ryo Nakabayashi;Daichi Yukihira

  • Advances in structure elucidation of small molecules using mass spectrometry

    Tobias Kind;Oliver Fiehn

  • Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

    Zijuan Lai;Hiroshi Tsugawa;Gert Wohlgemuth;Sajjan Mehta

  • A comprehensive urinary metabolomic approach for identifying kidney cancerr.

    Tobias Kind;Vladimir Tolstikov;Oliver Fiehn;Robert H. Weiss;Robert H. Weiss

  • Identification of small molecules using accurate mass MS/MS search.

    Tobias Kind;Hiroshi Tsugawa;Tomas Cajka;Yan Ma

  • Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors.

    Carsten Denkert;Jan Budczies;Tobias Kind;Wilko Weichert

  • Metabolite profiling of human colon carcinoma--deregulation of TCA cycle and amino acid turnover.

    Carsten Denkert;Jan Budczies;Wilko Weichert;Gert Wohlgemuth

  • Systematic Error Removal Using Random Forest for Normalizing Large-Scale Untargeted Lipidomics Data.

    Sili Fan;Tobias Kind;Tomas Cajka;Stanley L. Hazen

  • MetaMapp: mapping and visualizing metabolomic data by integrating information from biochemical pathways and chemical and mass spectral similarity.

    Dinesh K. Barupal;Pradeep Kumar Haldiya;Gert Wohlgemuth;Tobias Kind

  • MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics

    James G Jeffryes;James G Jeffryes;Ricardo L Colastani;Mona Elbadawi-Sidhu;Tobias Kind

  • Retip: retention time prediction for compound annotation in untargeted metabolomics

    Paolo Bonini;Tobias Kind;Hiroshi Tsugawa;Dinesh Kumar Barupal

  • Critical Assessment of Small Molecule Identification 2016: automated methods

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

  • Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification.

    Yuanyue Li;Tobias Kind;Jacob Folz;Arpana Vaniya

  • Structure Annotation of All Mass Spectra in Untargeted Metabolomics

    Ivana Blaženović;Tobias Kind;Michael R. Sa;Jian Ji

Frequent Co-Authors

Oliver Fiehn
Oliver Fiehn University of California, Davis
Manfred Dietel
Manfred Dietel Charité - University Medicine Berlin
Werner Brack
Werner Brack Helmholtz Centre for Environmental Research
Carsten Denkert
Carsten Denkert Philipp University of Marburg
Tomas Cajka
Tomas Cajka Czech Academy of Sciences
Wilko Weichert
Wilko Weichert Technical University of Munich
Vivian Hook
Vivian Hook University of California, San Diego
Henner Hollert
Henner Hollert Goethe University Frankfurt
Dieter Jahn
Dieter Jahn Technische Universität Braunschweig

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