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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Chemistry 53 12910 11614 61 53 102 14730

Tomas Cajka publications per year

The chart shows the history of publications by Tomas Cajka between 2003 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Tomas Cajka published across 23 years, from 2003 to 2025, averaging 7 papers a year. Output peaked at 18 publications in 2024. 30 of the 160 publications appeared in the last two years.

No. of publications
5 10 15
Bar chart. Horizontal axis: year, 2003 to 2025. Vertical axis: number of publications, 0 to 18. Peak 18 publications in 2024. 2003: 2 publications 2004: 2 publications 2005: 2 publications 2006: 3 publications 2007: 3 publications 2008: 5 publications 2009: 3 publications 2010: 5 publications 2011: 8 publications 2012: 6 publications 2013: 7 publications 2014: 4 publications 2015: 1 publication 2016: 12 publications 2017: 14 publications 2018: 8 publications 2019: 5 publications 2020: 9 publications 2021: 3 publications 2022: 11 publications 2023: 17 publications 2024: 18 publications 2025: 12 publications
2003 2025

160 publications in total across all disciplines

View publications per year as a table
Tomas Cajka: publications per year, 2003 to 2025
Year Publications
2003 2
2004 2
2005 2
2006 3
2007 3
2008 5
2009 3
2010 5
2011 8
2012 6
2013 7
2014 4
2015 1
2016 12
2017 14
2018 8
2019 5
2020 9
2021 3
2022 11
2023 17
2024 18
2025 12
Total 160
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Tomas Cajka 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 Tomas Cajka sits on this spectrum.

No. of scientists
250 500 750 1,000 1,250
Bar chart with 63 bars. Horizontal axis: publications, 61–80 to 1,295+. Vertical axis: number of scientists, 0 to 1,350. Most scientists, 1,350, have 161–180 publications. The last bar groups every scientist with 1,295 publications or more. The highlighted bar, 101–120 publications, is where this scientist sits. 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
61–80 publications 1,295+

This scientist: 102 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Chemistry scientists by publication count, Research.com 2026 ranking edition. Based on 17,934 ranked scientists.
Publications Scientists This scientist
61–80 66
81–100 302
101–120 623 102
121–140 918
141–160 1,218
161–180 1,350
181–200 1,344
201–220 1,281
221–240 1,216
241–260 1,100
261–280 979
281–300 939
301–320 764
321–340 643
341–360 628
361–380 522
381–400 459
401–420 397
421–440 327
441–460 270
461–480 265
481–500 252
501–520 201
521–540 185
541–560 148
561–580 148
581–600 132
601–620 114
621–640 104
641–660 91
661–680 92
681–700 73
701–720 57
721–740 54
741–760 67
761–780 45
781–800 46
801–820 39
821–840 32
841–860 36
861–880 29
881–900 26
901–920 24
921–940 14
941–960 23
961–980 28
981–1,000 15
1,001–1,020 29
1,021–1,040 12
1,041–1,060 19
1,061–1,080 12
1,081–1,100 6
1,101–1,120 8
1,121–1,140 12
1,141–1,160 5
1,161–1,180 6
1,181–1,200 14
1,201–1,220 7
1,221–1,240 2
1,241–1,260 6
1,261–1,280 4
1,281–1,294 6
1,295+ 100
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Tomas Cajka 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 Tomas Cajka sits on this spectrum.

No. of scientists
250 500 750 1,000
Bar chart with 61 bars. Horizontal axis: D-Index, 40–41 to 159+. Vertical axis: number of scientists, 0 to 1,051. Most scientists, 1,051, have 56–57 D-Index. The last bar groups every scientist with 159 D-Index or more. The highlighted bar, 52–53 D-Index, is where this scientist sits. 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
40–41 D-Index 159+

This scientist: 53 D-Index — 28th percentile

28% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Chemistry scientists by D-index, Research.com 2026 ranking edition. Based on 17,934 ranked scientists.
D-Index Scientists This scientist
40–41 289
42–43 612
44–45 808
46–47 776
48–49 835
50–51 861
52–53 872 53
54–55 933
56–57 1,051
58–59 930
60–61 882
62–63 834
64–65 731
66–67 775
68–69 683
70–71 646
72–73 561
74–75 501
76–77 437
78–79 388
80–81 354
82–83 292
84–85 275
86–87 254
88–89 235
90–91 185
92–93 192
94–95 155
96–97 163
98–99 125
100–101 105
102–103 105
104–105 112
106–107 88
108–109 68
110–111 69
112–113 65
114–115 79
116–117 61
118–119 44
120–121 37
122–123 40
124–125 33
126–127 26
128–129 34
130–131 35
132–133 25
134–135 27
136–137 17
138–139 16
140–141 20
142–143 20
144–145 15
146–147 9
148–149 9
150–151 16
152–153 11
154–155 9
156–157 3
158 3
159+ 98
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Overview

Tomas Cajka is affiliated with the Czech Academy of Sciences in the Czech Republic. The scientist's research work primarily focuses on Medicine and Biochemistry, Genetics and Molecular Biology, with notable contributions to subfields including Molecular Biology, Physiology, Spectroscopy, Nutrition and Dietetics, and Cancer Research.

Their recent papers cover a range of topics within metabolomics and cardiovascular health, published in high-impact journals. Noteworthy publications include:

  • A lipidome atlas in MS-DIAL 4, 2020, Nature Biotechnology
  • A Cardiovascular Disease-Linked Gut Microbial Metabolite Acts via Adrenergic Receptors, 2020, Cell
  • The artificial sweetener erythritol and cardiovascular event risk, 2023, Nature Medicine
  • A terminal metabolite of niacin promotes vascular inflammation and contributes to cardiovascular disease risk, 2024, Nature Medicine
  • Distinct roles of adipose triglyceride lipase and hormone-sensitive lipase in the catabolism of triacylglycerol estolides, 2020, Proceedings of the National Academy of Sciences

Frequent co-authorship occurs with the following researchers:

  • Ondřej Kuda (21 coauthored publications)
  • Oliver Fiehn (15 coauthored publications)
  • Ján Kopecký (14 coauthored publications)
  • Martin Rossmeisl (13 coauthored publications)
  • Andrea Beňová (10 coauthored publications)

Tomas Cajka's work appears regularly in several scientific venues, including:

  • Zenodo (CERN European Organization for Nuclear Research) with 5 publications
  • Nature Medicine with 3 publications
  • TrAC Trends in Analytical Chemistry with 3 publications
  • bioRxiv (Cold Spring Harbor Laboratory) with 3 publications
  • International Journal of Molecular Sciences with 2 publications

The main research topics addressed by Tomas Cajka encompass:

  • Metabolomics and Mass Spectrometry Studies
  • Adipose Tissue and Metabolism
  • Mass Spectrometry Techniques and Applications
  • Diet and metabolism studies
  • Fatty Acid Research and Health
  • Liver Disease Diagnosis and Treatment
  • Advanced Proteomics Techniques and Applications

Best Publications

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

    Hiroshi Tsugawa;Tomas Cajka;Tobias Kind;Yan Ma

  • Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics.

    Tomas Cajka;Oliver Fiehn;Oliver Fiehn

  • A lipidome atlas in MS-DIAL 4.

    Hiroshi Tsugawa;Kazutaka Ikeda;Mikiko Takahashi;Aya Satoh

  • Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry

    Tomas Cajka;Oliver Fiehn

  • A Cardiovascular Disease-Linked Gut Microbial Metabolite Acts via Adrenergic Receptors.

    Ina Nemet;Ina Nemet;Prasenjit Prasad Saha;Prasenjit Prasad Saha;Nilaksh Gupta;Nilaksh Gupta;Weifei Zhu;Weifei Zhu

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

    Hiroshi Tsugawa;Tobias Kind;Ryo Nakabayashi;Daichi Yukihira

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

    Tobias Kind;Hiroshi Tsugawa;Tomas Cajka;Yan Ma

  • Challenging applications offered by direct analysis in real time (DART) in food-quality and safety analysis

    Jana Hajslova;Tomas Cajka;Lukas Vaclavik

  • Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma.

    John A. Bowden;Alan Heckert;Candice Z. Ulmer;Christina M. Jones

  • Ambient mass spectrometry employing direct analysis in real time (DART) ion source for olive oil quality and authenticity assessment.

    Lukas Vaclavik;Tomas Cajka;Vojtech Hrbek;Jana Hajslova

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

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

  • Validating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography–High-Resolution Mass Spectrometry Platforms

    Tomas Cajka;Jennifer T. Smilowitz;Oliver Fiehn;Oliver Fiehn

  • Aroma profiles of five basil (Ocimum basilicum L.) cultivars grown under conventional and organic conditions

    Eva Klimánková;Kateřina Holadová;Jana Hajšlová;Tomáš Čajka

  • Critical assessment of extraction methods for the simultaneous determination of pesticide residues and mycotoxins in fruits, cereals, spices and oil seeds employing ultra-high performance liquid chromatography-tandem mass spectrometry.

    Ondrej Lacina;Milena Zachariasova;Jana Urbanova;Marta Vaclavikova

  • Tracing the geographical origin of honeys based on volatile compounds profiles assessment using pattern recognition techniques

    I. Stanimirova;B. Üstün;T. Cajka;K. Riddelova

  • Streamlining sample preparation and gas chromatography-tandem mass spectrometry analysis of multiple pesticide residues in tea.

    Tomas Cajka;Chris Sandy;Veronika Bachanova;Lucie Drabova

  • Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography–Mass Spectroscopy (LC-MS) Data Processing

    Brian C. DeFelice;Sajjan Singh Mehta;Stephanie Samra;Tomáš Čajka

  • Recognition of beer brand based on multivariate analysis of volatile fingerprint

    Tomas Cajka;Katerina Riddellova;Monika Tomaniova;Jana Hajslova

  • Rapid analysis of multiple pesticide residues in fruit-based baby food using programmed temperature vaporiser injection-low-pressure gas chromatography-high-resolution time-of-flight mass spectrometry.

    Tomas Cajka;Jana Hajslova;Ondrej Lacina;Katerina Mastovska

  • Evaluation of two-dimensional gas chromatography-time-of-flight mass spectrometry for the determination of multiple pesticide residues in fruit.

    Jitka Zrostlı́ková;Jana Hajšlová;Tomáš Čajka

Frequent Co-Authors

Oliver Fiehn
Oliver Fiehn University of California, Davis
Jana Hajslova
Jana Hajslova University of Chemistry and Technology
J. Bruce German
J. Bruce German University of California, Davis
Kermit L. Carraway
Kermit L. Carraway University of California, Davis
Stanley L. Hazen
Stanley L. Hazen Cleveland Clinic Lerner College of Medicine
W.H. Wilson Tang
W.H. Wilson Tang Cleveland Clinic
Tobias Kind
Tobias Kind University of California, Davis
Rudolf Zechner
Rudolf Zechner University of Graz
Tomas Randak
Tomas Randak Masaryk University

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