Limei Ai

433 citations
25 papers · 326 · h-index 9

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Multiple Myeloma Research and Treatments

Papers in

    • CRISPR and Genetic Engineering 3
    • Viral Infectious Diseases and Gene Expression in Insects 2
    • Histone Deacetylase Inhibitors Research 2
    • Microbial Metabolic Engineering and Bioproduction 2
    • Lymphoma Diagnosis and Treatment 2

Limei Ai

24 papers receiving 320 citations

Peers

Limei Ai
Comparison fields: 5 of 66
  • Cancer Research 70
  • Hematology 48
  • Pharmacology 30
  • Molecular Biology 190
  • Genetics 27
Replace Makoto Irie with:
Makoto Irie Japan
Eleana Harmel-Laws United States
Chansu Lee South Korea
Nikki A. Evensen United States
Nitika Sharma United States
Yang He China
Eun‐Yup Lee South Korea
Shaolin Ma China
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Citations per field
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Makoto Irie · 1×
Citations per year

Countries citing papers authored by Limei Ai

Since Specialization
Citations

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

Fields of papers citing papers by Limei Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201675
2 201755
3 201354
4 201727
5 202025
6 201514
7 202513
8 201810
9 20138
10 20198
11 20247
12 20156
13 20195
14 20224
15 20223
16 20242
17
[Survival and prognosis of patients with polycythemia vera: a study of 816 patients in a single Chinese center].
20152
18 20192
19 20231
20
[Inhibition of TLR4 represses proliferation and invasion ability of Raji lymphoma cells].
20181

About Limei Ai

Limei Ai is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Hematology, Cancer Research and Pharmacology, having authored 25 papers that have together received 326 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (3 papers), Ferroptosis and cancer prognosis (2 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (2 papers), CAR-T cell therapy research (2 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Histone Deacetylase Inhibitors Research (2 papers), Lymphoma Diagnosis and Treatment (2 papers) and Microbial Metabolic Engineering and Bioproduction (2 papers). The work is most often cited by research in Cancer Research (70 citations), Hematology (48 citations), Pharmacology (30 citations), Molecular Biology (190 citations) and Genetics (27 citations). Limei Ai has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Shanshan Yu, Wei Wei, Wei Sun, Yang Yu, Ning Zhang, Jing Pan, Jing Pan, Shanshan Yu, Wei Wei and Yuanyuan Sun. Their work appears in journals such as Tumor Biology, Biology Direct, Xenobiotica, Current Microbiology and Frontiers in Immunology.

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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