Sa Wang

5.2k citations
85 papers · 2.7k · h-index 26

Impact in

  • Hematology top 1%
    • Acute Myeloid Leukemia Research
    • Autoimmune and Inflammatory Disorders Research
    • Chronic Myeloid Leukemia Treatments
    • SARS-CoV-2 detection and testing
    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies

Papers in

    • Acute Myeloid Leukemia Research 11
    • Autoimmune and Inflammatory Disorders Research 4
    • Chronic Myeloid Leukemia Treatments 4

Sa Wang

82 papers receiving 2.7k citations

Peers

Sa Wang
Comparison fields: 5 of 135
  • Hematology 645
  • Infectious Diseases 499
  • Genetics 233
  • Immunology 341
  • Oncology 407
Replace Jialan Shi with:
Jialan Shi United States
James F. Beck Germany
Tomasz Wróbel Poland
Kouhei Yamashita Japan
Guoqing Wei China
Kuniaki Seyama Japan
Jianmin Wang China
William Bellamy United States
Nobuhiko Emi Japan
Zheng Yin China
Sa Wang relative to Jialan Shi United States Jialan Shi's profile →
Citations per field
00.5×1.5×
Jialan Shi · 1×
Citations per year

Countries citing papers authored by Sa Wang

Since Specialization
Citations

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

Fields of papers citing papers by Sa Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020480
2 1999156
3 2017150
4 1998134
5 2000129
6 2016113
7 2019106
8 201283
9 201683
10 202377
11 201876
12 201574
13 201668
14 202060
15 201658
16 200455
17 201149
18 201648
19 200341
20 200637

About Sa Wang

Sa Wang is a scholar working on Molecular Biology, Hematology, Pathology and Forensic Medicine, Immunology and Infectious Diseases, having authored 85 papers that have together received 2.7k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (11 papers), Acute Lymphoblastic Leukemia research (7 papers), Lymphoma Diagnosis and Treatment (7 papers), Chronic Lymphocytic Leukemia Research (6 papers), COVID-19 Clinical Research Studies (4 papers), Autoimmune and Inflammatory Disorders Research (4 papers), Chronic Myeloid Leukemia Treatments (4 papers) and Immune Response and Inflammation (3 papers). The work is most often cited by research in Hematology (645 citations), Infectious Diseases (499 citations), Genetics (233 citations), Immunology (341 citations) and Oncology (407 citations). Sa Wang has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Hagop M. Kantarjian, Fujie Zhang, Guiju Gao, Gloria C. Li, Fengting Yu, Siyuan Yang, Chianru Tan, Yong Guo, Carlos Cordon‐Cardo and David J. Chen. Their work appears in journals such as Blood, Cancer, Archives of Pathology & Laboratory Medicine, American Journal of Hematology and Modern Pathology.

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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