Qingzhao Zhang

2.2k total citations
103 papers, 1.5k citations indexed

About

Qingzhao Zhang is a scholar working on Statistics and Probability, Molecular Biology and Genetics. According to data from OpenAlex, Qingzhao Zhang has authored 103 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Statistics and Probability, 38 papers in Molecular Biology and 14 papers in Genetics. Recurrent topics in Qingzhao Zhang's work include Statistical Methods and Inference (39 papers), Gene expression and cancer classification (28 papers) and Bioinformatics and Genomic Networks (17 papers). Qingzhao Zhang is often cited by papers focused on Statistical Methods and Inference (39 papers), Gene expression and cancer classification (28 papers) and Bioinformatics and Genomic Networks (17 papers). Qingzhao Zhang collaborates with scholars based in China, United States and Japan. Qingzhao Zhang's co-authors include Paul W. Kincade, Shuangge Ma, Robert S. Welner, Brandt L. Esplin, Patrick C. Wilson, Lisa Borghesi, Tomoyuki Shimazu, Karla P. Garrett, Kenneth G. C. Smith and Melissa Mathias and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and The Journal of Experimental Medicine.

In The Last Decade

Qingzhao Zhang

90 papers receiving 1.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Qingzhao Zhang China	19	744	354	219	155	131	103	1.5k
Elizabeth Mansfield United States	20	894 1.2×	1.4k 4.1×	185 0.8×	145 0.9×	79 0.6×	30	2.2k
Stephen Ward United Kingdom	12	1.1k 1.5×	485 1.4×	71 0.3×	299 1.9×	34 0.3×	19	2.0k
Nicki Panoskaltsis United Kingdom	21	1.1k 1.4×	769 2.2×	407 1.9×	322 2.1×	34 0.3×	76	2.8k
Bernard Prum France	20	405 0.5×	422 1.2×	66 0.3×	128 0.8×	27 0.2×	36	1.4k
Jing Fu China	28	445 0.6×	1.2k 3.3×	95 0.4×	52 0.3×	51 0.4×	80	2.5k
Lisa M. Maier United States	20	1.1k 1.5×	668 1.9×	71 0.3×	68 0.4×	139 1.1×	21	2.6k
Anna Bergamaschi United States	23	490 0.7×	1.3k 3.8×	57 0.3×	76 0.5×	153 1.2×	42	2.7k
Oxana K. Pickeral United States	12	761 1.0×	1.1k 3.1×	133 0.6×	138 0.9×	61 0.5×	16	2.3k
J. Michael Hamilton United States	19	544 0.7×	697 2.0×	48 0.2×	81 0.5×	80 0.6×	38	1.6k
D. Ioannides Greece	31	372 0.5×	120 0.3×	95 0.4×	25 0.2×	112 0.9×	110	2.6k

Countries citing papers authored by Qingzhao Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Qingzhao Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingzhao Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Qingzhao Zhang. A scholar is included among the top collaborators of Qingzhao Zhang 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 Qingzhao Zhang. Qingzhao Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Shen, Chong, et al.. (2025). Genetic variants in PD-1 and its ligands, gene–gene and gene–environment interactions in allergic rhinitis. International Immunopharmacology. 147. 113912–113912.

Fang, Kuangnan, et al.. (2024). Community influence analysis in social networks. Computational Statistics & Data Analysis. 202. 108037–108037. 2 indexed citations

Zhang, Qingzhao, et al.. (2023). Gene–environment interaction analysis via deep learning. Genetic Epidemiology. 47(3). 261–286. 8 indexed citations

Zhang, Qingzhao, et al.. (2023). Pathological Imaging-Assisted Cancer Gene–Environment Interaction Analysis. Biometrics. 79(4). 3883–3894. 4 indexed citations

Chen, Ruoxi, Qingzhao Zhang, Meiping Lu, et al.. (2022). TLR Signaling Pathway Gene Polymorphisms, Gene–Gene and Gene–Environment Interactions in Allergic Rhinitis. Journal of Inflammation Research. Volume 15. 3613–3630. 8 indexed citations

Li, Shuang, Xue Lü, Qingzhao Zhang, et al.. (2021). Dose-effect relationships of ¹²C⁶⁺ ions-induced dicentric plus ring chromosomes, micronucleus and nucleoplasmic bridges in human lymphocytes in vitro. International Journal of Radiation Biology. 97(5). 657–663. 1 indexed citations

Zhang, Qingzhao, et al.. (2021). Assisted estimation of gene expression graphical models. Genetic Epidemiology. 45(4). 372–385.

Zhang, Xiaochen, et al.. (2021). Multivariate functional generalized additive models. Journal of Statistical Computation and Simulation. 92(4). 875–893. 4 indexed citations

Liu, Yan, Sanguo Zhang, Shuangge Ma, & Qingzhao Zhang. (2020). Tests for regression coefficients in high dimensional partially linear models. Statistics & Probability Letters. 163. 108772–108772. 8 indexed citations

10.

Zhang, Qingzhao, et al.. (2020). Squamous Neoplasia in the Esophagus. Archives of Pathology & Laboratory Medicine. 145(5). 554–561. 9 indexed citations

11.

Zhang, Qingzhao, Gloria Young, & Zhaohai Yang. (2019). Pure Discrete Punctate Nuclear Staining Pattern for MLH1 Protein Does Not Represent Intact Nuclear Expression. International Journal of Surgical Pathology. 28(2). 146–152. 11 indexed citations

12.

Fan, Xinyan, et al.. (2019). Assisted graphical model for gene expression data analysis. Statistics in Medicine. 38(13). 2364–2380. 1 indexed citations

13.

Ma, Yue, Tao Xu, Qingzhao Zhang, et al.. (2018). Nicotine Enhances Staphylococcus epidermidis Biofilm Formation by Altering the Bacterial Autolysis, Extracellular DNA Releasing, and Polysaccharide Intercellular Adhesin Production. Frontiers in Microbiology. 9. 2575–2575. 19 indexed citations

14.

Wu, Mengyun, et al.. (2018). Robust identification of gene-environment interactions for prognosis using a quantile partial correlation approach. Genomics. 111(5). 1115–1123. 15 indexed citations

15.

Zhang, Qingzhao, Ryuji Iida, Takafumi Yokota, & Paul W. Kincade. (2013). Early events in lymphopoiesis. Current Opinion in Hematology. 20(4). 265–272. 12 indexed citations

16.

Andrews, Sarah F., Qingzhao Zhang, Lie Li, et al.. (2012). Global analysis of B cell selection using an immunoglobulin light chain–mediated model of autoreactivity. The Journal of Experimental Medicine. 210(1). 125–142. 19 indexed citations

17.

Shimazu, Tomoyuki, Ryuji Iida, Qingzhao Zhang, et al.. (2012). CD86 is expressed on murine hematopoietic stem cells and denotes lymphopoietic potential. Blood. 119(21). 4889–4897. 33 indexed citations

18.

Esplin, Brandt L., Tomoyuki Shimazu, Robert S. Welner, et al.. (2011). Chronic Exposure to a TLR Ligand Injures Hematopoietic Stem Cells. The Journal of Immunology. 186(9). 5367–5375. 265 indexed citations

19.

Duty, J. Andrew, Péter Szodoray, Nai‐Ying Zheng, et al.. (2008). Functional anergy in a subpopulation of naive B cells from healthy humans that express autoreactive immunoglobulin receptors. The Journal of Experimental Medicine. 206(1). 139–151. 183 indexed citations

20.

Koelsch, Kristi A., Nai-Ying Zheng, Qingzhao Zhang, et al.. (2007). Mature B cells class switched to IgD are autoreactive in healthy individuals. Journal of Clinical Investigation. 117(6). 1558–1565. 109 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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