Daibing Zhou

589 total citations
27 papers, 414 citations indexed

About

Daibing Zhou is a scholar working on Oncology, Molecular Biology and Epidemiology. According to data from OpenAlex, Daibing Zhou has authored 27 papers receiving a total of 414 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 9 papers in Molecular Biology and 7 papers in Epidemiology. Recurrent topics in Daibing Zhou's work include TGF-β signaling in diseases (5 papers), Tuberculosis Research and Epidemiology (3 papers) and Mycobacterium research and diagnosis (3 papers). Daibing Zhou is often cited by papers focused on TGF-β signaling in diseases (5 papers), Tuberculosis Research and Epidemiology (3 papers) and Mycobacterium research and diagnosis (3 papers). Daibing Zhou collaborates with scholars based in China, Canada and Australia. Daibing Zhou's co-authors include Jian Ma, Guoxiong Xu, Weimin Ren, Lingyun Zhang, Wencai Guan, Shengqing Li, Wenwen Sun, Jihong Zhang, Jimin Shi and Lubna Nadeem and has published in prestigious journals such as Journal of Clinical Oncology, Scientific Reports and Medicine.

In The Last Decade

Daibing Zhou

22 papers receiving 394 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daibing Zhou China 10 151 102 91 69 59 27 414
Fiona O’Connell Ireland 10 84 0.6× 20 0.2× 44 0.5× 111 1.6× 132 2.2× 33 460
Rui Fu China 11 82 0.5× 10 0.1× 31 0.3× 60 0.9× 34 0.6× 43 432
Jiaqi Cui China 12 136 0.9× 34 0.3× 46 0.5× 82 1.2× 95 1.6× 50 495
Claudia Hurtado Chile 10 202 1.3× 54 0.5× 73 0.8× 116 1.7× 22 0.4× 27 421
Ayushi Verma India 11 176 1.2× 50 0.5× 58 0.6× 68 1.0× 50 0.8× 33 376
D Hafler United States 8 132 0.9× 20 0.2× 38 0.4× 113 1.6× 68 1.2× 9 1.1k
Jinxian Chen China 14 316 2.1× 12 0.1× 207 2.3× 114 1.7× 19 0.3× 33 596
Rajeev Pandey United States 10 115 0.8× 22 0.2× 80 0.9× 57 0.8× 18 0.3× 24 326
Huai‐Hsuan Huang Taiwan 11 200 1.3× 14 0.1× 89 1.0× 48 0.7× 37 0.6× 27 467
George A. Komatsoulis United States 12 355 2.4× 19 0.2× 63 0.7× 76 1.1× 85 1.4× 28 622

Countries citing papers authored by Daibing Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Daibing Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daibing Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Daibing Zhou. A scholar is included among the top collaborators of Daibing 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 Daibing Zhou. Daibing Zhou 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.
Zhang, Xiujuan, Dong Liang, Ning Zhu, et al.. (2025). The interplay between M2-like macrophages and Th17.1 cells promotes the progression of early-stage sarcoidosis. Cell Communication and Signaling. 24(1). 1–1.
2.
Zhang, You‐Zhi, Xiujuan Zhang, Jing Wang, et al.. (2025). Characterizations of lung cancer microbiome and exploration of potential microbial risk factors for lung cancer. Scientific Reports. 15(1). 15683–15683.
3.
Hong, Cheng, Daibing Zhou, Xiaofeng Wu, et al.. (2025). Pulmonary Artery Stent Implantation for Fibrosing Mediastinitis: Our Clinical Experience. Pulmonary Circulation. 15(2). e70076–e70076.
4.
5.
Zhou, Daibing, et al.. (2023). Characteristics and Comparison of Rapidly Growing and Slowly Growing nontuberculous Mycobacterial Pulmonary Disease. International Journal of Mycobacteriology. 12(3). 324–331. 2 indexed citations
6.
Zhang, Xiujuan, Yu Zhao, Ning Zhu, et al.. (2023). CDK10 suppresses metastasis of lung adenocarcinoma through inhibition of the ETS2/c‐Raf/p‐MEK/p‐ERK signaling loop. Molecular Carcinogenesis. 63(1). 61–74. 5 indexed citations
7.
Zhou, Daibing, et al.. (2023). Identification and comparison of Chlamydia psittaci, Legionella and Mycoplasma pneumonia infection. The Clinical Respiratory Journal. 17(5). 384–393. 9 indexed citations
8.
Zhou, Daibing, et al.. (2023). Performance of mNGS in bronchoalveolar lavage fluid for the diagnosis of invasive pulmonary aspergillosis in non-neutropenic patients. Frontiers in Cellular and Infection Microbiology. 13. 1271853–1271853. 10 indexed citations
9.
Zhang, Xiujuan, Yuanyuan Zhang, Kun Chen, et al.. (2022). Diagnostic efficiency and safety of rapidon‐siteevaluation combined withCT‐guidedtransthoracic core needle biopsy in suspected lung cancer patients. Cytopathology. 33(4). 439–444. 9 indexed citations
10.
Dong, Liang, Xinning Liu, Bo Wu, et al.. (2022). Mxi1-0 Promotes Hypoxic Pulmonary Hypertension Via ERK/c-Myc-dependent Proliferation of Arterial Smooth Muscle Cells. Frontiers in Genetics. 13. 810157–810157. 11 indexed citations
11.
Wang, Jing, Xiujuan Zhang, Ning Zhu, et al.. (2022). Protein tyrosine phosphatase PTPL1 suppresses lung cancer through Src/ERK/YAP1 signaling. Thoracic Cancer. 13(21). 3042–3051. 3 indexed citations
12.
Zhou, Daibing, et al.. (2021). Diagnostic Accuracy of Metagenomic Next‐Generation Sequencing in Sputum‐Scarce or Smear‐Negative Cases with Suspected Pulmonary Tuberculosis. BioMed Research International. 2021(1). 9970817–9970817. 20 indexed citations
13.
Shi, Jimin, Lingyun Zhang, Daibing Zhou, et al.. (2018). Biological Function of Ribosomal Protein L10 on Cell Behavior in Human Epithelial Ovarian Cancer. Journal of Cancer. 9(4). 745–756. 25 indexed citations
14.
Guan, Wencai, Lingyun Zhang, Wenwen Sun, et al.. (2018). Physical interaction of STAT1 isoforms with TGF-β receptors leads to functional crosstalk between two signaling pathways in epithelial ovarian cancer. Journal of Experimental & Clinical Cancer Research. 37(1). 103–103. 46 indexed citations
15.
Zhang, Lingyun, Daibing Zhou, Wencai Guan, et al.. (2017). Pyridoxine 5′-phosphate oxidase is a novel therapeutic target and regulated by the TGF-β signalling pathway in epithelial ovarian cancer. Cell Death and Disease. 8(12). 3214–3214. 65 indexed citations
16.
Zhou, Daibing, Lingyun Zhang, Wenwen Sun, et al.. (2017). Cytidine monophosphate kinase is inhibited by the TGF-β signalling pathway through the upregulation of miR-130b-3p in human epithelial ovarian cancer. Cellular Signalling. 35. 197–207. 31 indexed citations
17.
18.
Zhang, Jihong, Daibing Zhou, Lingyun Zhang, et al.. (2017). Dual Effects of N,N-dimethylformamide on Cell Proliferation and Apoptosis in Breast Cancer. Dose-Response. 15(4). 3794093165–3794093165. 15 indexed citations
19.
Sun, Wenwen, et al.. (2016). Human epithelial-type ovarian tumour marker beta-2-microglobulin is regulated by the TGF-β signaling pathway. Journal of Translational Medicine. 14(1). 75–75. 19 indexed citations
20.
L, Li, et al.. (1991). [Research on thixotropic properties of whole blood in patients with ischemic stroke and its high risk].. PubMed. 22(1). 4–7.

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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