Faming Zhu

3.4k total citations
412 papers, 2.1k citations indexed

About

Faming Zhu is a scholar working on Immunology, Hematology and Genetics. According to data from OpenAlex, Faming Zhu has authored 412 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 298 papers in Immunology, 79 papers in Hematology and 36 papers in Genetics. Recurrent topics in Faming Zhu's work include Immune Cell Function and Interaction (280 papers), T-cell and B-cell Immunology (279 papers) and Immunotherapy and Immune Responses (222 papers). Faming Zhu is often cited by papers focused on Immune Cell Function and Interaction (280 papers), T-cell and B-cell Immunology (279 papers) and Immunotherapy and Immune Responses (222 papers). Faming Zhu collaborates with scholars based in China, United States and Malaysia. Faming Zhu's co-authors include Ji He, L.‐X. Yan, Xianguo Xu, W. Zhang, Lina Dong, Xiaozhen Hong, H.‐J. Lv, Sudan Tao, Yanling Ying and Wei Zhang and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Antimicrobial Agents and Chemotherapy.

In The Last Decade

Faming Zhu

369 papers receiving 2.0k citations

Peers

Faming Zhu
Sergio Arce United States
David Peritt United States
Joanna Warren United States
David Stephany United States
Rachel D. Kuns Australia
Faming Zhu
Citations per year, relative to Faming Zhu Faming Zhu (= 1×) peers Jorge Esparza-Gordillo

Countries citing papers authored by Faming Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Faming Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faming Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Faming Zhu. A scholar is included among the top collaborators of Faming Zhu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Faming Zhu. Faming Zhu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
He, Yizhen, et al.. (2025). The Novel HLA ‐E Allele, HLA ‐E*01:01:46, Identified in a Chinese Individual. HLA. 105(5). e70254–e70254.
3.
He, Ji, et al.. (2025). Identification of the Novel HLA ‐C*03:641 Allele in a Chinese Cord Blood Donor. HLA. 105(5). e70207–e70207.
5.
Chen, Chen, et al.. (2025). Characterisation of the Novel HLA‐B*48:43:02 Allele in a Chinese Individual. HLA. 105(4). e70194–e70194.
6.
Wang, Fang, et al.. (2025). Identification of the Novel HLA‐B*55:141 Allele in a Chinese Individual. HLA. 105(5). e70246–e70246.
8.
Chen, Chen, Fang Wang, Ying Li, Wei Zhang, & Faming Zhu. (2025). Characterisation of the Novel HLADQA1*05:06:02 Allele by Next‐Generation Sequencing. HLA. 106(2). e70368–e70368. 1 indexed citations
9.
He, Ji, et al.. (2025). The Novel Allele HLA ‐A*26:01:80 Was Identified in a Chinese Individual. HLA. 105(4). e70187–e70187.
10.
He, Ji, et al.. (2024). Identification of the novel HLA‐DRB1*11:298 allele in a Chinese cord blood donor. HLA. 103(5). e15513–e15513. 1 indexed citations
11.
He, Ji, et al.. (2024). Identification of the novel HLA‐A*29:171 allele by next‐generation sequencing. HLA. 103(1). e15326–e15326. 2 indexed citations
12.
Wang, Fang, et al.. (2024). Identification of the novel HLA‐DQB1*06:466 allele by next‐generation sequencing in a Chinese cord blood donor. HLA. 103(5). e15497–e15497. 1 indexed citations
13.
Li, Ying, et al.. (2024). The novel HLA‐DPA1*02:86 allele was identified by next‐generation sequencing. HLA. 103(5). e15504–e15504. 1 indexed citations
14.
Chen, Chen, Yizhen He, Lina Dong, Wei Zhang, & Faming Zhu. (2023). Characterization of the novel HLA‐A*33 allele, HLA‐A*33:03:55 in a Chinese individual. HLA. 102(2). 224–226. 3 indexed citations
15.
Dong, Lina, et al.. (2023). Description of two new HLA alleles, HLA‐A*26:01:70 and HLA‐A*26:01:74 in Chinese individuals. HLA. 102(2). 218–221. 3 indexed citations
16.
Wang, Fang, et al.. (2023). Description of two new HLA‐C alleles, HLA‐C*15:245 and HLA‐C*15:246, identified in Chinese individuals. HLA. 102(3). 373–375. 2 indexed citations
17.
Tao, Sudan, et al.. (2023). The novel allele, HLA‐B*15:627 was identified by next‐generation sequencing in a Chinese cord blood donor. HLA. 103(1). e15309–e15309. 2 indexed citations
18.
Wang, Fang, Lina Dong, Wei Wang, et al.. (2021). The polymorphism of HLA‐A, ‐C, ‐B, ‐DRB3/4/5, ‐DRB1, ‐DQB1 loci in Zhejiang Han population, China using NGS technology. International Journal of Immunogenetics. 48(6). 485–489. 78 indexed citations
19.
Zhu, Faming, Peng Zhu, Lin Q, et al.. (2019). Resting-state functional magnetic resonance imaging (fMRI) and functional connectivity density mapping in patients with corneal ulcer. SHILAP Revista de lepidopterología. 2 indexed citations
20.
Huang, Yao, et al.. (2007). Decorin gene transfer inhibited the expression of TGFbeta1 and ECM in rat mesangial cells.. PubMed. 12(8). 360–8. 16 indexed citations

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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