Xiao Ming Yang

401 citations
4 papers · 318 · h-index 3

Impact in

    • DNA Repair Mechanisms
    • Cancer therapeutics and mechanisms
    • DNA and Nucleic Acid Chemistry
    • Advanced biosensing and bioanalysis techniques
    • Mitochondrial Function and Pathology
    • CRISPR and Genetic Engineering

Papers in

    • DNA Repair Mechanisms 1
    • DNA and Nucleic Acid Chemistry 1
    • Cancer therapeutics and mechanisms 1

Xiao Ming Yang

3 papers receiving 317 citations

Peers

Xiao Ming Yang
Comparison fields: 5 of 54
  • Molecular Biology 263
  • Cancer Research 42
  • Clinical Biochemistry 17
  • Oncology 63
  • Rheumatology 26
Replace Max Follettie with:
Max Follettie United States
Robert Gustafsson Sweden
Prasad Sulkshane Israel
Vinod Tiwari United States
Jennifer Bolsée Belgium
Victor H. Garritsen Netherlands
Lynne Ozgur United States
Rino Fukatsu Japan
Holly R. Thomas United States
Swagat Ray United Kingdom
Xiao Ming Yang relative to Max Follettie United States Max Follettie's profile →
Citations per field
00.5×1.7×
Max Follettie · 1×
Citations per year

Countries citing papers authored by Xiao Ming Yang

Since Specialization
Citations

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

Fields of papers citing papers by Xiao Ming Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao Ming Yang. 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 Ming Yang. The network helps show where Xiao Ming Yang may publish in the future.

Co-authors

The 10 scholars most cited alongside Xiao Ming Yang, 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 Ming Yang Line = papers co-authored together Xiao Ming Yang links everyone, so they are left out of the graph.

All Works

About Xiao Ming Yang

Xiao Ming Yang is a scholar working on Molecular Biology, Surgery, Oncology, Epidemiology and Clinical Biochemistry, having authored 4 papers that have together received 318 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (1 paper), DNA Repair Mechanisms (1 paper), Folate and B Vitamins Research (1 paper), Cancer Genomics and Diagnostics (1 paper), 3D Printing in Biomedical Research (1 paper), DNA and Nucleic Acid Chemistry (1 paper), Hepatitis B Virus Studies (1 paper) and Cancer therapeutics and mechanisms (1 paper). The work is most often cited by research in Molecular Biology (263 citations), Cancer Research (42 citations), Clinical Biochemistry (17 citations), Oncology (63 citations) and Rheumatology (26 citations). Xiao Ming Yang has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Dindial Ramotar, Dana D. Lasko, Arshad Jilani, Colin Ong, Stephen W. Scherer, Robert E. MacKenzie, Jian Wang, Miao Yu, Wěi Li and Feng Zhang. Their work appears in journals such as Nucleic Acids Research, Journal of Biological Chemistry, Biochemistry and Zhonghua fangshexian yixue zazhi.

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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