Mi Kwon

4.0k citations
114 papers · 1.2k · h-index 20

Impact in

Papers in

    • Hematopoietic Stem Cell Transplantation 51
    • Acute Myeloid Leukemia Research 18
    • CAR-T cell therapy research 20
    • Viral-associated cancers and disorders 9

Mi Kwon

105 papers receiving 1.2k citations

Peers

Mi Kwon
Comparison fields: 5 of 72
  • Hematology 542
  • Transplantation 50
  • Oncology 350
  • Immunology 191
  • Virology 40
Replace Bernardino Allione with:
Bernardino Allione Italy
Rémy Duléry France
Jaime Pérez de Oteyza Spain
Marcos J. de Lima United States
David Michonneau France
Woo-Sung Min South Korea
Claude‐Eric Bulabois France
Kana Sakamoto Japan
Christoph Groth Germany
Yener Koç Türkiye
Mi Kwon relative to Bernardino Allione Italy Bernardino Allione's profile →
Citations per field
00.5×5.4×
Bernardino Allione · 1×
Citations per year

Countries citing papers authored by Mi Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Mi Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201189
2 202186
3 201260
4 201455
5 201845
6 202145
7 201435
8 201834
9 202229
10 201925
11 201824
12 201224
13 201624
14 201424
15 202022
16 201922
17 202022
18 202321
19 202121
20 202020

About Mi Kwon

Mi Kwon is a scholar working on Hematology, Oncology, Public Health, Environmental and Occupational Health, Genetics and Immunology, having authored 114 papers that have together received 1.2k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (51 papers), CAR-T cell therapy research (20 papers), Acute Lymphoblastic Leukemia research (18 papers), Acute Myeloid Leukemia Research (18 papers), Lymphoma Diagnosis and Treatment (11 papers), Immune Cell Function and Interaction (10 papers), Viral-associated cancers and disorders (9 papers) and Mesenchymal stem cell research (8 papers). The work is most often cited by research in Hematology (542 citations), Transplantation (50 citations), Oncology (350 citations), Immunology (191 citations) and Virology (40 citations). Mi Kwon has collaborated with scholars based in Spain, United States and Germany. Frequent co-authors include José L. Díez‐Martín, Ismael Buño, Javier Anguita, Pascual Balsalobre, Carolina Martínez‐Laperche, David Serrano, Jorge Gayoso, Rebeca Bailén, Ana Pérez‐Corral and Nieves Dorado. Their work appears in journals such as Blood, Bone Marrow Transplantation, Biology of Blood and Marrow Transplantation, Frontiers in Immunology and Transplantation and Cellular 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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