Mikail Dogan

471 citations
9 papers · 239 · h-index 7

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 detection and testing
    • CAR-T cell therapy research
    • Cancer Cells and Metastasis

Papers in

    • CAR-T cell therapy research 6
    • Cancer Cells and Metastasis 2
    • SARS-CoV-2 and COVID-19 Research 3
    • COVID-19 Clinical Research Studies 2

Mikail Dogan

9 papers receiving 238 citations

Peers

Mikail Dogan
Comparison fields: 5 of 42
  • Infectious Diseases 107
  • Oncology 94
  • Immunology 65
  • Modeling and Simulation 9
  • Automotive Engineering 22
Replace Isabel Vogler with:
Isabel Vogler Germany
Lindsey Placek United States
Kenneth J. Olivier United States
Stephen D. O’Flanagan United States
Isadora T. Lape United States
Xingyue An United States
Lutz Gieselmann Germany
Ali Rezvan United States
Tara S. Abraham United States
Réka Lőrincz United States
Mikail Dogan relative to Isabel Vogler Germany Isabel Vogler's profile →
Citations per field
00.5×1.5×1.9×
Isabel Vogler · 1×
Citations per year

Countries citing papers authored by Mikail Dogan

Since Specialization
Citations

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

Fields of papers citing papers by Mikail Dogan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 202175
2 202242
3 202236
4 202131
5 201823
6 202221
7 20228
8 20222
9 20211

About Mikail Dogan

Mikail Dogan is a scholar working on Oncology, Infectious Diseases, Immunology, Biomedical Engineering and Molecular Biology, having authored 9 papers that have together received 239 indexed citations. Recurring topics across this work include CAR-T cell therapy research (6 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Immunotherapy and Immune Responses (2 papers), Cancer Cells and Metastasis (2 papers), COVID-19 Clinical Research Studies (2 papers), Immune Cell Function and Interaction (2 papers), 3D Printing in Biomedical Research (2 papers) and Phagocytosis and Immune Regulation (1 paper). The work is most often cited by research in Infectious Diseases (107 citations), Oncology (94 citations), Immunology (65 citations), Modeling and Simulation (9 citations) and Automotive Engineering (22 citations). Mikail Dogan has collaborated with scholars based in United States and Türkiye. Frequent co-authors include Derya Unutmaz, Lina Kozhaya, Lindsey Placek, Xin Chen, Madhuri Dey, İbrahim T. Özbolat, Myoung‐Hwan Kim, Michael Kleinberg, Ellen Klapper and Oral Alpan. Their work appears in journals such as Advanced Functional Materials, The Journal of Immunology, Inflammatory Bowel Diseases, Gastroenterology and Clinical & Translational 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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