Tim Kottke

1.8k citations
38 papers · 1.6k · h-index 21

Impact in

  • Immunology top 5%
    • Mast cells and histamine
    • Immunotherapy and Immune Responses
  • Genetics top 5%
    • Virus-based gene therapy research

Papers in

    • Mast cells and histamine 15
    • Immunotherapy and Immune Responses 11
    • Cancer Immunotherapy and Biomarkers 6

Tim Kottke

38 papers receiving 1.5k citations

Peers

Tim Kottke
Comparison fields: 5 of 73
  • Immunology 511
  • Genetics 471
  • Oncology 252
  • Computational Theory and Mathematics 106
  • Organic Chemistry 201
Replace Carole Fruchart‐Gaillard with:
Carole Fruchart‐Gaillard France
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Yeon‐Sun Seong South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Tim Kottke

Since Specialization
Citations

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

Fields of papers citing papers by Tim Kottke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008177
2 2022164
3 2009155
4 2020106
5
Viral fusogenic membrane glycoproteins kill solid tumor cells by nonapoptotic mechanisms that promote cross presentation of tumor antigens by dendritic cells.
2002103
6 201667
7 200364
8 200964
9 201162
10 200851
11 201450
12 201141
13 200735
14 200734
15 201034
16
Pharmacologically regulated production of targeted retrovirus from T cells for systemic antitumor gene therapy.
200333
17 200930
18 200624
19 201523
20 201722

About Tim Kottke

Tim Kottke is a scholar working on Immunology, Oncology, Genetics, Organic Chemistry and Cellular and Molecular Neuroscience, having authored 38 papers that have together received 1.6k indexed citations. Recurring topics across this work include Mast cells and histamine (15 papers), Immunotherapy and Immune Responses (11 papers), Virus-based gene therapy research (8 papers), Cancer Immunotherapy and Biomarkers (6 papers), Receptor Mechanisms and Signaling (4 papers), Synthesis and biological activity (4 papers), Computational Drug Discovery Methods (3 papers) and Neurotransmitter Receptor Influence on Behavior (2 papers). The work is most often cited by research in Immunology (511 citations), Genetics (471 citations), Oncology (252 citations), Computational Theory and Mathematics (106 citations) and Organic Chemistry (201 citations). Tim Kottke has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Holger Stark, Kerstin Sander, Richard G. Vile, Lilia Weizel, Alan A. Melcher, Jill Thompson, Kevin Joseph Harrington, Roland Seifert, Erich H. Schneider and Rosa María Díaz. Their work appears in journals such as Molecular Therapy, Bioorganic & Medicinal Chemistry Letters, Inflammation Research, Bioorganic & Medicinal Chemistry and Gene Therapy.

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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