Fenglin Wu

678 citations
55 papers · 390 · h-index 12

Impact in

    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology

Papers in

    • CAR-T cell therapy research 12
    • Immune Cell Function and Interaction 9
    • Immunotherapy and Immune Responses 5
    • T-cell and B-cell Immunology 4

Fenglin Wu

47 papers receiving 381 citations

Peers

Fenglin Wu
Comparison fields: 5 of 99
  • General Energy 9
  • Immunology 98
  • Oncology 113
  • Molecular Biology 116
  • Genetics 43
Replace Tieli Li with:
Tieli Li Japan
Zhaonian Hao China
Sisi Jin China
Jingmin Yu China
Wenjia Shi China
Shibing Li China
Jim Kling United States
Gabriele Anton Germany
Hongxia Wang China
Jay Ji United States
Fenglin Wu relative to Tieli Li Japan Tieli Li's profile →
Citations per field
00.5×10×15×20.6×
Tieli Li · 1×
Citations per year

Countries citing papers authored by Fenglin Wu

Since Specialization
Citations

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

Fields of papers citing papers by Fenglin Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202439
2 202338
3 201336
4 201820
5 201019
6 201219
7 202216
8 202015
9 201414
10 202013
11 201211
12 202311
13 201910
14 201210
15 20239
16 20168
17 20227
18 20237
19 20216
20 20226

About Fenglin Wu

Fenglin Wu is a scholar working on Oncology, Immunology, Molecular Biology, Genetics and Economics and Econometrics, having authored 55 papers that have together received 390 indexed citations. Recurring topics across this work include CAR-T cell therapy research (12 papers), Immune Cell Function and Interaction (9 papers), Market Dynamics and Volatility (6 papers), Immunotherapy and Immune Responses (5 papers), Virus-based gene therapy research (5 papers), T-cell and B-cell Immunology (4 papers), Quantum Computing Algorithms and Architecture (3 papers) and Quantum and electron transport phenomena (3 papers). The work is most often cited by research in General Energy (9 citations), Immunology (98 citations), Oncology (113 citations), Molecular Biology (116 citations) and Genetics (43 citations). Fenglin Wu has collaborated with scholars based in China. Frequent co-authors include Hongwei Shao, Wenfeng Zhang, Han Shen, Huaben Bo, Shulin Huang, Changli Tao, Jiaqi Zhou, Qizhu Chen, Wenli Ma and Yichen Liu. Their work appears in journals such as Physical review. A, Cancer Letters, Genes, International Review of Financial Analysis and Gene.

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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