Thomas Glück

2.1k citations
39 papers · 1.5k · h-index 20

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
  • Immunology top 10%
    • Immune Response and Inflammation

Papers in

    • SARS-CoV-2 and COVID-19 Research 5
    • Clostridium difficile and Clostridium perfringens research 2
    • Pneumonia and Respiratory Infections 3
    • Influenza Virus Research Studies 2

Thomas Glück

37 papers receiving 1.4k citations

Peers

Thomas Glück
Comparison fields: 5 of 154
  • Infectious Diseases 212
  • Immunology 209
  • Modeling and Simulation 43
  • Epidemiology 277
  • Electrochemistry 55
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Thomas Glück relative to Sadaki Inokuchi Japan Sadaki Inokuchi's profile →
Citations per field
00.5×3.6×
Sadaki Inokuchi · 1×
Citations per year

Countries citing papers authored by Thomas Glück

Since Specialization
Citations

This map shows the geographic impact of Thomas Glück'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 Thomas Glück with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Glück more than expected).

Fields of papers citing papers by Thomas Glück

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas Glück. 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 Thomas Glück. The network helps show where Thomas Glück may publish in the future.

Co-authors

The 25 scholars most cited alongside Thomas Glück, 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 Thomas Glück Line = papers co-authored together Thomas Glück links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003279
2 2013146
3 2009119
4 2020117
5
Immune status and risk for infection in patients receiving chronic immunosuppressive therapy.
2005111
6 200386
7 200464
8 201656
9 200549
10 200748
11 200847
12 202138
13 200734
14 200031
15 200829
16 202226
17 200525
18 202124
19 201824
20 200520

About Thomas Glück

Thomas Glück is a scholar working on Infectious Diseases, Epidemiology, Immunology, Surgery and Electrical and Electronic Engineering, having authored 39 papers that have together received 1.5k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), Immune Response and Inflammation (5 papers), Pneumonia and Respiratory Infections (3 papers), Electrodeposition and Electroless Coatings (3 papers), Extraction and Separation Processes (2 papers), Bacterial Infections and Vaccines (2 papers), Clostridium difficile and Clostridium perfringens research (2 papers) and Influenza Virus Research Studies (2 papers). The work is most often cited by research in Infectious Diseases (212 citations), Immunology (209 citations), Modeling and Simulation (43 citations), Epidemiology (277 citations) and Electrochemistry (55 citations). Thomas Glück has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Jianming Lü, David Dreisinger, Bernd Salzberger, Gerd Schmitz, Steven M. Opal, Gerhard Liebisch, Dieter Fröhlich, G. Rothe, Jürgen Schölmerich and Boris Ehrenstein. Their work appears in journals such as Infection, Intensive Care Medicine, Hydrometallurgy, Critical Care Medicine and Journal of Lipid Research.

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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