Ling Bei

760 citations
29 papers · 665 · h-index 17

Impact in

Papers in

    • Cancer-related gene regulation 9
    • Ubiquitin and proteasome pathways 6
    • Protein Tyrosine Phosphatases 4
    • Genomics and Chromatin Dynamics 4
    • RNA Research and Splicing 4
    • Cytokine Signaling Pathways and Interactions 6

Ling Bei

28 papers receiving 657 citations

Peers

Ling Bei
Comparison fields: 5 of 72
  • Hematology 169
  • Immunology 180
  • Immunology and Allergy 40
  • Molecular Biology 441
  • Genetics 67
Replace Kwok Peng Ng with:
Kwok Peng Ng United States
Lucia Gargiulo Italy
Abdelhafid Saci France
Tetsuharu Shinjyo Japan
Cristina Delgado-Martín United States
Jens Rüschmann Canada
Marie Cambot France
Deepa Shankar United States
Todd Ashworth United States
Ross Kinstrie United Kingdom
Ling Bei relative to Kwok Peng Ng United States Kwok Peng Ng's profile →
Citations per field
00.5×1.5×1.8×
Kwok Peng Ng · 1×
Citations per year

Countries citing papers authored by Ling Bei

Since Specialization
Citations

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

Fields of papers citing papers by Ling Bei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Ling 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 Ling Bei Line = papers co-authored together Ling Bei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200558
2 199850
3 200748
4 200844
5 200843
6 200339
7 201039
8 200238
9 201235
10 201127
11 199922
12 201122
13 201521
14 201518
15 201317
16 201817
17 201316
18 201615
19 201615
20 201214

About Ling Bei

Ling Bei is a scholar working on Molecular Biology, Oncology, Immunology, Hematology and Cancer Research, having authored 29 papers that have together received 665 indexed citations. Recurring topics across this work include Cancer-related gene regulation (9 papers), Cytokine Signaling Pathways and Interactions (6 papers), Ubiquitin and proteasome pathways (6 papers), Protein Tyrosine Phosphatases (4 papers), Genomics and Chromatin Dynamics (4 papers), RNA Research and Splicing (4 papers), Chronic Myeloid Leukemia Treatments (4 papers) and NF-κB Signaling Pathways (4 papers). The work is most often cited by research in Hematology (169 citations), Immunology (180 citations), Immunology and Allergy (40 citations), Molecular Biology (441 citations) and Genetics (67 citations). Ling Bei has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Elizabeth A. Eklund, Hao Wang, Weiqi Huang, Chirag Shah, Leonidas C. Platanias, Elizabeth Horvath, Xun Shen, Tianhui Hu, Zhong‐Ming Qian and Liping Hu. Their work appears in journals such as Journal of Biological Chemistry, Oncotarget, The Journal of Immunology, Oncogenesis and Leukemia.

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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