Sven Baumann

5.1k citations
89 papers · 3.9k indexed · h-index 34

Impact in

  • Immunology top 2%
    • Immune Cell Function and Interaction
    • Immune Response and Inflammation
    • Cell death mechanisms and regulation
    • Metabolomics and Mass Spectrometry Studies

Papers in

    • Immune Cell Function and Interaction 11
    • Immune Response and Inflammation 8
    • T-cell and B-cell Immunology 5

Sven Baumann

87 papers receiving 3.8k citations

Peers

Sven Baumann
Comparison fields: 5 of 146
  • Immunology 964
  • Molecular Biology 2.1k
  • Cancer Research 433
  • Spectroscopy 441
  • Oncology 572
Replace Yu Yu with:
Yu Yu China
Ping Wang China
Wenlin Huang China
Carmine Di Ilio Italy
Lijuan Liu China
Zhongzhou Chen China
Mingzhu Yin China
Joaquín Abián Spain
Motoko Takahashi Japan
Vijay K. Singh United States
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Citations per field
00.5×5.0×
Yu Yu · 1×
Citations per year

Countries citing papers authored by Sven Baumann

Since Specialization
Citations

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

Fields of papers citing papers by Sven Baumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20233
4 20211
5 201625
6 201634
7 201512
8 201533
9 201416
10 201470
11 201418
12 200991
13
Abstract 4099: Elevated Campesterol Serum Levels - a Significant Predictor of Incident Myocardial Infarction: Results of the Population-based MONICA/KORA Follow-up Study 1994 to 2005
200611
14 200664
15 200661
16 200638
17 200472
18 200354
19 20024
20 200254

About Sven Baumann

Sven Baumann is a scholar working on Immunology, Toxicology, Cancer Research, Spectroscopy and Molecular Biology, having authored 89 papers that have together received 3.9k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (13 papers), Cell death mechanisms and regulation (12 papers), Immune Cell Function and Interaction (11 papers), Advanced Proteomics Techniques and Applications (9 papers), NF-κB Signaling Pathways (8 papers), Immune Response and Inflammation (8 papers), Mass Spectrometry Techniques and Applications (6 papers) and T-cell and B-cell Immunology (5 papers). The work is most often cited by research in Immunology (964 citations), Molecular Biology (2.1k citations), Cancer Research (433 citations), Spectroscopy (441 citations) and Oncology (572 citations). Sven Baumann has collaborated with scholars based in Germany, Denmark and United States. Frequent co-authors include Peter H. Krammer, Andreas Krueger, Sabine Kirchhoff, Ingo Schmitz, Martin von Bergen�, Joachim Thiery, Uta Ceglarek, Martin Fiedler, Stefanie C. Fas and Alexander Leichtle. Their work appears in journals such as Blood, PLoS ONE, The Journal of Immunology, Journal of Clinical Investigation and European Journal of Immunology.

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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