Hai Yu

2.0k citations
34 papers · 1.7k · h-index 18

Impact in

Papers in

    • RNA Interference and Gene Delivery 9
    • Advanced biosensing and bioanalysis techniques 5
    • Immunotherapy and Immune Responses 9
    • Toxin Mechanisms and Immunotoxins 4
    • T-cell and B-cell Immunology 4

Hai Yu

33 papers receiving 1.7k citations

Peers

Hai Yu
Comparison fields: 5 of 117
  • Molecular Medicine 322
  • Biomaterials 286
  • Immunology 409
  • Cancer Research 232
  • Biomedical Engineering 555
Replace Ruixia Hou with:
Ruixia Hou China
Rohan Fernandes United States
Jinfeng Cao China
Kun Shi China
Ariella Shikanov United States
Zhong‐Kai Cui China
Gerard J. Madlambayan United States
Volkan Yesilyurt United States
Alireza Hassani Najafabadi United States
Ruoyu Cheng China
Hai Yu relative to Ruixia Hou China Ruixia Hou's profile →
Citations per field
00.5×3.4×
Ruixia Hou · 1×
Citations per year

Countries citing papers authored by Hai Yu

Since Specialization
Citations

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

Fields of papers citing papers by Hai Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012232
2 2020210
3 2021142
4 2019138
5 2011133
6 2022120
7 2018102
8 2004100
9 200991
10 200173
11 200667
12 200251
13 201045
14 202142
15 200729
16 202223
17 200421
18 200421
19 200615
20 200415

About Hai Yu

Hai Yu is a scholar working on Molecular Biology, Immunology, Genetics, Biomedical Engineering and Molecular Medicine, having authored 34 papers that have together received 1.7k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (9 papers), RNA Interference and Gene Delivery (9 papers), Virus-based gene therapy research (7 papers), Advanced biosensing and bioanalysis techniques (5 papers), Hydrogels: synthesis, properties, applications (5 papers), Advanced Materials and Mechanics (4 papers), Toxin Mechanisms and Immunotoxins (4 papers) and T-cell and B-cell Immunology (4 papers). The work is most often cited by research in Molecular Medicine (322 citations), Biomaterials (286 citations), Immunology (409 citations), Cancer Research (232 citations) and Biomedical Engineering (555 citations). Hai Yu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Zi Liang Wu, Miao Du, Xuetao Cao, Qingqing Wang, Qiang Zheng, Si Yu Zheng, Jianli Wang, Yinjing Song, Guping Tang and Hongliang Huang. Their work appears in journals such as Immunology Letters, Advanced Materials, Chemical Communications, ACS Applied Materials & Interfaces and Cancer.

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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