Peigen Zhou

781 total citations
14 papers, 481 citations indexed

About

Peigen Zhou is a scholar working on Infectious Diseases, Molecular Biology and Statistics and Probability. According to data from OpenAlex, Peigen Zhou has authored 14 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Infectious Diseases, 3 papers in Molecular Biology and 3 papers in Statistics and Probability. Recurrent topics in Peigen Zhou's work include SARS-CoV-2 and COVID-19 Research (3 papers), Statistical Methods and Bayesian Inference (2 papers) and Statistical Methods and Inference (2 papers). Peigen Zhou is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (3 papers), Statistical Methods and Bayesian Inference (2 papers) and Statistical Methods and Inference (2 papers). Peigen Zhou collaborates with scholars based in United States, China and Australia. Peigen Zhou's co-authors include Tengchuan Jin, Huan Ma, Weihong Zeng, Dan Zhao, Linzhao Cheng, Hongliang He, Yajuan Li, Xiaoling Ma, Wei‐Yin Loh and Luxi Cao and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Virology and Journal of the Atmospheric Sciences.

In The Last Decade

Peigen Zhou

14 papers receiving 474 citations

Peers

Peigen Zhou
Yifei Guo China
Peigen Zhou
Citations per year, relative to Peigen Zhou Peigen Zhou (= 1×) peers Yifei Guo

Countries citing papers authored by Peigen Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Peigen Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peigen Zhou

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

All Works

14 of 14 papers shown
1.
Bajor, David L., Martin Gutierrez, Gina M. Vaccaro, et al.. (2022). Preliminary results of a phase 1 study of sea-CD40, gemcitabine, nab-paclitaxel, and pembrolizumab in patients with metastatic pancreatic ductal adenocarcinoma (PDAC).. Journal of Clinical Oncology. 40(4_suppl). 559–559. 6 indexed citations
2.
Ma, Huan, Weihong Zeng, Xiangzhi Meng, et al.. (2021). Potent Neutralization of SARS-CoV-2 by Hetero-Bivalent Alpaca Nanobodies Targeting the Spike Receptor-Binding Domain. Journal of Virology. 95(10). 50 indexed citations
3.
Loh, Wei‐Yin & Peigen Zhou. (2021). Variable Importance Scores. Journal of Data Science. 569–592. 31 indexed citations
4.
Patnaik, Amita, Emiliano Calvo, Sarina A. Piha‐Paul, et al.. (2021). A phase 1 study of SGN-B6A, an antibody-drug conjugate targeting integrin beta-6, in patients with advanced solid tumors (SGNB6A-001, Trial in Progress).. Journal of Clinical Oncology. 39(15_suppl). TPS3144–TPS3144. 5 indexed citations
5.
Ma, Huan, Weihong Zeng, Hongliang He, et al.. (2020). Serum IgA, IgM, and IgG responses in COVID-19. Cellular and Molecular Immunology. 17(7). 773–775. 303 indexed citations
6.
Ma, Huan, Dan Zhao, Weihong Zeng, et al.. (2020). Decline of SARS-CoV-2-specific IgG, IgM and IgA in convalescent COVID-19 patients within 100 days after hospital discharge. Science China Life Sciences. 64(3). 482–485. 22 indexed citations
7.
Zheng, Ye, Peigen Zhou, & Sündüz Keleş. (2020). FreeHi-C spike-in simulations for benchmarking differential chromatin interaction detection. Methods. 189. 3–11. 1 indexed citations
8.
Si, Yajuan & Peigen Zhou. (2020). Bayes-Raking: Bayesian Finite Population Inference with Known Margins. Journal of Survey Statistics and Methodology. 9(4). 833–855. 7 indexed citations
9.
Loh, Wei‐Yin, Luxi Cao, & Peigen Zhou. (2019). Subgroup identification for precision medicine: A comparative review of 13 methods. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 9(5). 39 indexed citations
10.
Back, Larissa E., et al.. (2019). Boundary Layer Quasi-Equilibrium Limits Convective Intensity Enhancement from the Diurnal Cycle in Surface Heating. Journal of the Atmospheric Sciences. 77(1). 217–237. 6 indexed citations
11.
Xu, Jiao, et al.. (2018). Role of IL-33 and ST2 signaling and inflammatory responses in non-small cell lung cancer. Tropical Journal of Pharmaceutical Research. 17(5). 767–767. 1 indexed citations
12.
Zhou, Peigen, et al.. (2014). microRNA-449a Suppresses Non-small Cell Lung Cancer. Cell Biochemistry and Biophysics. 71(2). 1255–1259. 7 indexed citations
13.
Guan, Rui, et al.. (2000). p53 and K-ras gene mutations in lung cancer of workers exposed to silica and asbestos. Lung Cancer. 29(1). 211–211. 1 indexed citations
14.
Zhou, Peigen, et al.. (1997). [A preliminary study on p53 gene in lung cancer tissues of workers exposed to silica and welding fumes].. PubMed. 31(3). 153–6. 2 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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