Yi Bei

887 citations
7 papers · 76 · h-index 4

Impact in

Papers in

    • RNA Research and Splicing 2
    • Ubiquitin and proteasome pathways 2
    • Signaling Pathways in Disease 1
    • Protein Degradation and Inhibitors 1
    • Cholesterol and Lipid Metabolism 1

Yi Bei

7 papers receiving 76 citations

Peers

Yi Bei
Comparison fields: 5 of 29
  • Cancer Research 15
  • Cell Biology 15
  • Molecular Biology 61
  • Hematology 8
  • Neurology 6
Replace Apurva M. Hegde with:
Apurva M. Hegde United States
Camilla Borges Ferreira Gomes United States
Daniel Hüebschmann Germany
Yilun Ma United States
Caterina Lucano Italy
Saritha Tantravedi United States
Harshal Shah United States
Jens Wittner Germany
Bridget E. Begg United States
Tina Giese United States
Yi Bei relative to Apurva M. Hegde United States Apurva M. Hegde's profile →
Citations per field
00.5×
Apurva M. Hegde · 1×
Citations per year

Countries citing papers authored by Yi Bei

Since Specialization
Citations

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

Fields of papers citing papers by Yi Bei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 201825
2 201920
3 201917
4
[Knockdown of nuclear protein 1 (NUPR1) gene inhibits proliferation and promotes apoptosis of human multiple myeloma U266 cells].
201710
5 20242
6 20251
7
Clinical observations on the treatment of 98 cases of peptic ulcer by massage.
19931

About Yi Bei

Yi Bei is a scholar working on Molecular Biology, Surgery, Neurology, Health, Toxicology and Mutagenesis and Complementary and alternative medicine, having authored 7 papers that have together received 76 indexed citations. Recurring topics across this work include RNA Research and Splicing (2 papers), Ubiquitin and proteasome pathways (2 papers), interferon and immune responses (1 paper), Signaling Pathways in Disease (1 paper), Protein Degradation and Inhibitors (1 paper), Cholesterol and Lipid Metabolism (1 paper), Cancer Research and Treatments (1 paper) and Cancer, Lipids, and Metabolism (1 paper). The work is most often cited by research in Cancer Research (15 citations), Cell Biology (15 citations), Molecular Biology (61 citations), Hematology (8 citations) and Neurology (6 citations). Yi Bei has collaborated with scholars based in China, Germany and Russia. Frequent co-authors include Xingxin Li, Xi Huang, Xi Peng, Heathcliff Dorado García, Jianbin Chen, Angelika Eggert, Johannes H. Schulte, Anton G. Henssen, Alex Kentsis and Filippos Klironomos. Their work appears in journals such as Frontiers in Pharmacology, JCI Insight, Cancer Letters, Oncology Reports and PubMed.

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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