Dahui Qin

2.2k total citations · 1 hit paper
37 papers, 1.6k citations indexed

About

Dahui Qin is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Dahui Qin has authored 37 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 9 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in Dahui Qin's work include Immunotherapy and Immune Responses (11 papers), T-cell and B-cell Immunology (10 papers) and Cancer Genomics and Diagnostics (6 papers). Dahui Qin is often cited by papers focused on Immunotherapy and Immune Responses (11 papers), T-cell and B-cell Immunology (10 papers) and Cancer Genomics and Diagnostics (6 papers). Dahui Qin collaborates with scholars based in United States, China and France. Dahui Qin's co-authors include John G. Tew, Jiuhua Wu, Andras K. Szakal, Gregory F. Burton, A K Szakal, Shirley Helm, Jeffrey V. Ravetch, Tim Manser, Kalpit A. Vora and Judith C. McCaffrey and has published in prestigious journals such as Journal of Clinical Investigation, The Journal of Immunology and PLoS ONE.

In The Last Decade

Dahui Qin

34 papers receiving 1.6k citations

Hit Papers

Nonenzymatic lysine d-lactylation induced by glyoxalase I... 2025 2026 2025 5 10 15 20
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Nonenzymatic lysine d-lactylation induced by glyoxalase II substrate SLG dampens inflammatory immune responses
    2025 24 citations Qiang Wang, Qinghua Yao et al. Cell Research profile →

Peers

Dahui Qin
Irene Puga United States
Laurence Ménard United States
Julia I. Ellyard Australia
Robert T. Woodland United States
Tineke Cantaert Netherlands
Judith L. McKenzie New Zealand
A. Amadori Italy
Andrew Getahun United States
Barry D. Hock New Zealand
Elizabeth E. Eynon United States
Irene Puga United States
Dahui Qin
Citations per year, relative to Dahui Qin Dahui Qin (= 1×) peers Irene Puga

Countries citing papers authored by Dahui Qin

Since Specialization
Citations

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

Fields of papers citing papers by Dahui Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dahui Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Dahui Qin. A scholar is included among the top collaborators of Dahui Qin 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 Dahui Qin. Dahui Qin 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
1.
Berglund, Anders, John Puskas, Sean Yoder, et al.. (2025). Evaluating the Radiation Sensitivity Index and 12-Chemokine Gene Expression Signature for Clinical Use in a CLIA Laboratory. Cancer Research Communications. 5(3). 389–397. 2 indexed citations
2.
Wang, Qiang, Qinghua Yao, Wenfang Li, et al.. (2025). Nonenzymatic lysine d-lactylation induced by glyoxalase II substrate SLG dampens inflammatory immune responses. Cell Research. 35(2). 97–116. 24 indexed citations breakdown →
3.
4.
5.
Qin, Dahui. (2021). Molecular testing for acute myeloid leukemia. Cancer Biology and Medicine. 18(-). 0–0. 7 indexed citations
6.
Song, Jinming, Mohammad Hussaini, Dahui Qin, et al.. (2020). Comparison of SF3B1/DNMT3A Comutations With DNMT3A or SF3B1 Mutation Alone in Myelodysplastic Syndrome and Clonal Cytopenia of Undetermined Significance. American Journal of Clinical Pathology. 154(1). 48–56. 5 indexed citations
7.
Saller, James J., Dahui Qin, Seth Felder, & Domenico Coppola. (2020). Microsatellite Stable Colorectal Cancer With an Immunogenic Phenotype: Challenges in Diagnosis and Treatment. Clinical Colorectal Cancer. 19(2). 123–131. 2 indexed citations
8.
Qin, Dahui. (2019). Next-generation sequencing and its clinical application. Cancer Biology and Medicine. 16(1). 4–10. 174 indexed citations
9.
Song, Jinming, Mohammad Hussaini, Hailing Zhang, et al.. (2016). Comparison of the Mutational Profiles of Primary Myelofibrosis, Polycythemia Vera, and Essential Thrombocytosis. American Journal of Clinical Pathology. 147(5). 444–452. 30 indexed citations
10.
Davies, Kurtis D., Midhat S. Farooqi, Mike Gruidl, et al.. (2016). Multi-Institutional FASTQ File Exchange as a Means of Proficiency Testing for Next-Generation Sequencing Bioinformatics and Variant Interpretation. Journal of Molecular Diagnostics. 18(4). 572–579. 19 indexed citations
11.
Li, Ao, Yuan Li, Dan Liang, et al.. (2014). Loss of Polycystin-1 Inhibits Bicc1 Expression during Mouse Development. PLoS ONE. 9(3). e88816–e88816. 13 indexed citations
12.
Qin, Dahui, et al.. (2012). Pyrosequencing data analysis software: a useful tool for EGFR, KRAS, and BRAF mutation analysis. Diagnostic Pathology. 7(1). 56–56. 21 indexed citations
13.
Tanvetyanon, Tawee, Dahui Qin, Tapan Padhya, et al.. (2008). Survival outcomes of squamous cell carcinoma arising from sinonasal inverted papilloma: report of 6 cases with systematic review and pooled analysis. American Journal of Otolaryngology. 30(1). 38–43. 57 indexed citations
14.
Tew, John G., et al.. (2001). Follicular dendritic cells: beyond the necessity of T-cell help. Trends in Immunology. 22(7). 361–367. 114 indexed citations
15.
Wu, Jiuhua, et al.. (2001). Follicular dendritic cell accessory activity crosses MHC and species barriers. European Journal of Immunology. 31(1). 176–185. 22 indexed citations
16.
Qin, Dahui, Jiuhua Wu, Kalpit A. Vora, et al.. (2000). Fcγ Receptor IIB on Follicular Dendritic Cells Regulates the B Cell Recall Response. The Journal of Immunology. 164(12). 6268–6275. 146 indexed citations
17.
Qin, Dahui, Jiuhua Wu, Gregory F. Burton, Andras K. Szakal, & John G. Tew. (1999). Follicular dendritic cells mediated maintenance of primary lymphocyte cultures for long-term analysis of a functional in vitro immune system. Journal of Immunological Methods. 226(1-2). 19–27. 19 indexed citations
18.
Kapasi, Zoher F., Dahui Qin, William G. Kerr, et al.. (1998). Follicular Dendritic Cell (FDC) Precursors in Primary Lymphoid Tissues. The Journal of Immunology. 160(3). 1078–1084. 78 indexed citations
19.
Qin, Dahui, Jiuhua Wu, Gregory F. Burton, A K Szakal, & John G. Tew. (1997). A Role for CR2 in FDC-B Cell Interactions. Advances in experimental medicine and biology. 417. 493–497. 5 indexed citations
20.
Tew, John G., Jiuhua Wu, Dahui Qin, et al.. (1997). Follicular dendritic cells and presentation of antigen and costimulatory signals to B cells. Immunological Reviews. 156(1). 39–52. 192 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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