Michael Gabl

1.2k citations
31 papers · 883 · h-index 19

Impact in

  • Immunology top 10%
    • Immune Response and Inflammation
    • Neutrophil, Myeloperoxidase and Oxidative Mechanisms
  • Microbiology top 10%

Papers in

    • S100 Proteins and Annexins 23
    • Receptor Mechanisms and Signaling 6
    • Immune Response and Inflammation 15
    • Neutrophil, Myeloperoxidase and Oxidative Mechanisms 6

Michael Gabl

31 papers receiving 875 citations

Peers

Michael Gabl
Comparison fields: 5 of 73
  • Immunology 309
  • Microbiology 59
  • Cellular and Molecular Neuroscience 150
  • Molecular Biology 528
  • Physiology 32
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Michael Gabl relative to Gregory Cherryholmes United States Gregory Cherryholmes's profile →
Citations per field
00.5×6.5×
Gregory Cherryholmes · 1×
Citations per year

Countries citing papers authored by Michael Gabl

Since Specialization
Citations

This map shows the geographic impact of Michael Gabl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Gabl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Gabl more than expected).

Fields of papers citing papers by Michael Gabl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Gabl. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Gabl. The network helps show where Michael Gabl may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Gabl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Gabl Line = papers co-authored together Michael Gabl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016123
2 201098
3 200562
4 201251
5 201744
6 201843
7 201440
8 201436
9 201636
10 201827
11 201526
12 201926
13 202026
14 201424
15 201723
16 202121
17 201520
18 201818
19 201618
20 201617

About Michael Gabl

Michael Gabl is a scholar working on Molecular Biology, Immunology, Cancer Research, Cellular and Molecular Neuroscience and Microbiology, having authored 31 papers that have together received 883 indexed citations. Recurring topics across this work include S100 Proteins and Annexins (23 papers), Immune Response and Inflammation (15 papers), Protease and Inhibitor Mechanisms (8 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (6 papers), Receptor Mechanisms and Signaling (6 papers), Neuropeptides and Animal Physiology (6 papers), Antimicrobial Peptides and Activities (5 papers) and Spine and Intervertebral Disc Pathology (3 papers). The work is most often cited by research in Immunology (309 citations), Microbiology (59 citations), Cellular and Molecular Neuroscience (150 citations), Molecular Biology (528 citations) and Physiology (32 citations). Michael Gabl has collaborated with scholars based in Sweden, United States and Denmark. Frequent co-authors include Huamei Forsman, Cláes Dahlgren, André Holdfeldt, Malene Winther, Martina Sundqvist, Johan Bylund, Jonas Mårtensson, Karin Christenson, Klaus Galiano and Alois Obwegeser. Their work appears in journals such as The Journal of Immunology, Biochemical Pharmacology, Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, PLoS ONE and Journal of Leukocyte Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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