Xiao‐Dong Mo

4.9k citations
253 papers · 2.9k indexed · h-index 30

Impact in

Papers in

    • Hematopoietic Stem Cell Transplantation 162
    • Acute Myeloid Leukemia Research 82
    • Renal Transplantation Outcomes and Treatments 23

Xiao‐Dong Mo

208 papers receiving 2.9k citations

Peers

Xiao‐Dong Mo
Comparison fields: 5 of 97
  • Hematology 2.3k
  • Transplantation 190
  • Immunology 840
  • Genetics 343
  • Oncology 798
Replace Hee‐Je Kim with:
Hee‐Je Kim South Korea
Chen‐Hua Yan China
Chang‐Ki Min South Korea
Byung‐Sik Cho South Korea
Kazuhiro Ikegame Japan
Jean El Cheikh France
Alida Dominietto Italy
Jaime Sanz Spain
Kazuteru Ohashi Japan
Kyoo‐Hyung Lee South Korea
Xiao‐Dong Mo relative to Hee‐Je Kim South Korea Hee‐Je Kim's profile →
Citations per field
00.5×1.7×
Hee‐Je Kim · 1×
Citations per year

Countries citing papers authored by Xiao‐Dong Mo

Since Specialization
Citations

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

Fields of papers citing papers by Xiao‐Dong Mo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao‐Dong Mo. 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 Xiao‐Dong Mo. The network helps show where Xiao‐Dong Mo may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 253 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015148
2 2017113
3 201685
4 201664
5 202160
6 200958
7 202156
8 201749
9 202049
10 201949
11 201748
12 201448
13 201546
14 201845
15 201945
16 201544
17 201644
18 201340
19 201939
20 201639

About Xiao‐Dong Mo

Xiao‐Dong Mo is a scholar working on Hematology, Transplantation, Immunology, Genetics and Oncology, having authored 253 papers that have together received 2.9k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (162 papers), Acute Myeloid Leukemia Research (82 papers), Acute Lymphoblastic Leukemia research (55 papers), Polyomavirus and related diseases (32 papers), Immune Cell Function and Interaction (26 papers), T-cell and B-cell Immunology (25 papers), Cytomegalovirus and herpesvirus research (24 papers) and Renal Transplantation Outcomes and Treatments (23 papers). The work is most often cited by research in Hematology (2.3k citations), Transplantation (190 citations), Immunology (840 citations), Genetics (343 citations) and Oncology (798 citations). Xiao‐Dong Mo has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Xiao‐Jun Huang, Lan‐Ping Xu, Yu Wang, Xiaohui Zhang, Kai‐Yan Liu, Yu‐Hong Chen, Huan Chen, Chen‐Hua Yan, Feng‐Rong Wang and Ying‐Jun Chang. Their work appears in journals such as Bone Marrow Transplantation, Annals of Hematology, Blood, Biology of Blood and Marrow Transplantation and British Journal of Haematology.

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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