Jun Kong

645 citations
47 papers · 402 · h-index 12

Impact in

  • Hematology top 5%
    • Hematopoietic Stem Cell Transplantation
    • Acute Myeloid Leukemia Research
    • CAR-T cell therapy research
    • Neutropenia and Cancer Infections

Papers in

    • Hematopoietic Stem Cell Transplantation 16
    • Acute Myeloid Leukemia Research 12
    • Chronic Myeloid Leukemia Treatments 6
    • Multiple Myeloma Research and Treatments 5
    • Immune Cell Function and Interaction 9
    • T-cell and B-cell Immunology 4

Jun Kong

38 papers receiving 395 citations

Peers

Jun Kong
Comparison fields: 5 of 59
  • Hematology 165
  • Oncology 107
  • Immunology 78
  • Epidemiology 97
  • Genetics 20
Replace Chiaki Kato with:
Chiaki Kato Japan
Pınar Ataca Atilla Türkiye
Yuju Ohno Japan
Sameh Ayari France
Joanne Filicko-O’Hara United States
Mair Pedro de Souza Brazil
Amin T. Turki Germany
Ayumi Numata Japan
Valkal Bhatt United States
Emilia Jaskuła Poland
Jun Kong relative to Chiaki Kato Japan Chiaki Kato's profile →
Citations per field
00.5×2.8×
Chiaki Kato · 1×
Citations per year

Countries citing papers authored by Jun Kong

Since Specialization
Citations

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

Fields of papers citing papers by Jun Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201572
2 201847
3 201740
4 202123
5 202120
6 202019
7 201418
8 202417
9 201916
10 201816
11 202115
12 201712
13 202410
14 202110
15 20228
16 20218
17 20237
18 20206
19 20215
20 20194

About Jun Kong

Jun Kong is a scholar working on Hematology, Immunology, Epidemiology, Oncology and Public Health, Environmental and Occupational Health, having authored 47 papers that have together received 402 indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (16 papers), Acute Myeloid Leukemia Research (12 papers), Immune Cell Function and Interaction (9 papers), Cytomegalovirus and herpesvirus research (7 papers), Chronic Myeloid Leukemia Treatments (6 papers), Acute Lymphoblastic Leukemia research (5 papers), Multiple Myeloma Research and Treatments (5 papers) and T-cell and B-cell Immunology (4 papers). The work is most often cited by research in Hematology (165 citations), Oncology (107 citations), Immunology (78 citations), Epidemiology (97 citations) and Genetics (20 citations). Jun Kong has collaborated with scholars based in China, Malaysia and Japan. Frequent co-authors include Xiao‐Jun Huang, Lan‐Ping Xu, Yu Wang, Chen‐Hua Yan, Kai‐Yan Liu, Yuqian Sun, Xiaohui Zhang, Bin Shan, Yifei Cheng and Feng‐Rong Wang. Their work appears in journals such as Blood, British Journal of Haematology, Bone Marrow Transplantation, Annals of Hematology and Frontiers in Oncology.

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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