Maike Reith

614 citations
6 papers · 449 · h-index 5

Impact in

  • Immunology top 10%
    • Immune cells in cancer
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
  • Oncology top 10%
    • Cancer Immunotherapy and Biomarkers
    • CAR-T cell therapy research
    • Cancer Cells and Metastasis

Papers in

    • S100 Proteins and Annexins 3
    • Pluripotent Stem Cells Research 2
    • CRISPR and Genetic Engineering 2
    • Renal and related cancers 1
    • Immunotherapy and Immune Responses 1
    • Immune cells in cancer 1

Maike Reith

6 papers receiving 447 citations

Peers

Maike Reith
Comparison fields: 5 of 39
  • Immunology 221
  • Oncology 241
  • Clinical Biochemistry 22
  • Molecular Biology 145
  • Cancer Research 29
Replace Kathrin Tarnanidis with:
Kathrin Tarnanidis Germany
Da Qian China
Amir H. Ameri United States
Yingying Sun China
Ya-Chin Hou Taiwan
Ulrike Naumann Switzerland
Kunpeng Lv China
Johan Forssell Sweden
Song Wei China
Xiaozhang Xu China
Maike Reith relative to Kathrin Tarnanidis Germany Kathrin Tarnanidis's profile →
Citations per field
00.5×1.5×
Kathrin Tarnanidis · 1×
Citations per year

Countries citing papers authored by Maike Reith

Since Specialization
Citations

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

Fields of papers citing papers by Maike Reith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

6 of 6 papers shown
#Work
1 2015292
2 201969
3 201732
4 201530
5 201624
6 20142

About Maike Reith

Maike Reith is a scholar working on Molecular Biology, Immunology, Clinical Biochemistry, Biomedical Engineering and Infectious Diseases, having authored 6 papers that have together received 449 indexed citations. Recurring topics across this work include S100 Proteins and Annexins (3 papers), Pluripotent Stem Cells Research (2 papers), CRISPR and Genetic Engineering (2 papers), Advanced Glycation End Products research (1 paper), Immunotherapy and Immune Responses (1 paper), 3D Printing in Biomedical Research (1 paper), Immune cells in cancer (1 paper) and Renal and related cancers (1 paper). The work is most often cited by research in Immunology (221 citations), Oncology (241 citations), Clinical Biochemistry (22 citations), Molecular Biology (145 citations) and Cancer Research (29 citations). Maike Reith has collaborated with scholars based in Germany, Switzerland and China. Frequent co-authors include Jochen Utikal, Christoffer Gebhardt, Viktor Umansky, Tim Holland‐Letz, Kathrin Tarnanidis, Ramtin Lichtenberger, Dirk Schadendorf, Antje Sucker, Ludmila Umansky and Philipp Beckhove. Their work appears in journals such as Journal of Clinical Oncology, Clinical Cancer Research, International Journal of Cancer, Journal for ImmunoTherapy of Cancer and Stem Cell Reports.

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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