Shu Xing

3.0k citations
90 papers · 2.4k · h-index 27

Impact in

  • Genetics top 1%
    • Myeloproliferative Neoplasms: Diagnosis and Treatment
  • Hematology top 2%
    • Chronic Myeloid Leukemia Treatments
    • Acute Myeloid Leukemia Research

Papers in

    • Protein Tyrosine Phosphatases 23
    • Advanced biosensing and bioanalysis techniques 21
    • RNA Interference and Gene Delivery 7
    • DNA and Nucleic Acid Chemistry 6
    • Galectins and Cancer Biology 7

Shu Xing

86 papers receiving 2.4k citations

Peers

Shu Xing
Comparison fields: 5 of 121
  • Genetics 783
  • Hematology 472
  • Rheumatology 362
  • Molecular Biology 1.4k
  • Cancer Research 238
Replace Paul J. Shami with:
Paul J. Shami United States
Pingda Ren United States
Herman Burger Netherlands
David Rodrı́guez Spain
Jinyun Liu United States
Carlo Leonetti Italy
Dimitris Georgiadis Greece
Daniel L. Baker United States
Frank D. Böhmer Germany
M. V. Ramana Reddy United States
Shu Xing relative to Paul J. Shami United States Paul J. Shami's profile →
Citations per field
00.5×1.5×2.2×
Paul J. Shami · 1×
Citations per year

Countries citing papers authored by Shu Xing

Since Specialization
Citations

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

Fields of papers citing papers by Shu Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005480
2 2008159
3 2006107
4 2006100
5 199086
6 201284
7 201984
8 201362
9 202054
10 202152
11 201251
12 201849
13 201547
14 201043
15 201441
16 201239
17 201238
18 201037
19 201137
20 201236

About Shu Xing

Shu Xing is a scholar working on Molecular Biology, Immunology, Materials Chemistry, Cancer Research and Organic Chemistry, having authored 90 papers that have together received 2.4k indexed citations. Recurring topics across this work include Protein Tyrosine Phosphatases (23 papers), Advanced biosensing and bioanalysis techniques (21 papers), Galectins and Cancer Biology (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (7 papers), RNA Interference and Gene Delivery (7 papers), Vanadium and Halogenation Chemistry (6 papers), Biosensors and Analytical Detection (6 papers) and DNA and Nucleic Acid Chemistry (6 papers). The work is most often cited by research in Genetics (783 citations), Hematology (472 citations), Rheumatology (362 citations), Molecular Biology (1.4k citations) and Cancer Research (238 citations). Shu Xing has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Xueqi Fu, Zhizhuang Joe Zhao, Sanford B. Krantz, Qingshan Li, Zhe Li, Runxiang Zhao, Liping Lu, Miaoli Zhu, Caixia Yuan and Mengjia Xu. Their work appears in journals such as Dalton Transactions, Journal of Biological Chemistry, RSC Advances, Chemical Communications and BioMetals.

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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