Ming-Yi Zhou

572 total citations
20 papers, 447 citations indexed

About

Ming-Yi Zhou is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Oncology. According to data from OpenAlex, Ming-Yi Zhou has authored 20 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Endocrinology, Diabetes and Metabolism, 6 papers in Surgery and 5 papers in Oncology. Recurrent topics in Ming-Yi Zhou's work include Hormonal Regulation and Hypertension (11 papers), Estrogen and related hormone effects (4 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (3 papers). Ming-Yi Zhou is often cited by papers focused on Hormonal Regulation and Hypertension (11 papers), Estrogen and related hormone effects (4 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (3 papers). Ming-Yi Zhou collaborates with scholars based in United States, China and Argentina. Ming-Yi Zhou's co-authors include Elise P. Gómez-Sánchez, Celso E. Gómez-Sánchez, Wen‐Chieh Lin, Eduardo N. Cozza, Mark F. Foecking, Hiroyuki Morita, Danbo Wang, Damián G. Romero, Venkataseshu K. Ganjam and Srihari Thanigaraj and has published in prestigious journals such as Journal of Clinical Oncology, Food Chemistry and Endocrinology.

In The Last Decade

Ming-Yi Zhou

20 papers receiving 439 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming-Yi Zhou United States 14 225 109 85 60 53 20 447
Rucha Patel Canada 11 135 0.6× 268 2.5× 108 1.3× 80 1.3× 71 1.3× 16 640
Abdullah Ösme United States 15 106 0.5× 240 2.2× 112 1.3× 31 0.5× 68 1.3× 25 556
Chunsheng Xia United States 9 266 1.2× 268 2.5× 357 4.2× 176 2.9× 109 2.1× 16 731
Bert Kadereit Switzerland 9 116 0.5× 214 2.0× 54 0.6× 12 0.2× 32 0.6× 9 461
Victor K. Khor United States 10 81 0.4× 226 2.1× 79 0.9× 42 0.7× 82 1.5× 13 632
Sang R. Lee South Korea 14 56 0.2× 155 1.4× 30 0.4× 43 0.7× 69 1.3× 29 487
Eduardo Hideo Gilglioni Brazil 14 74 0.3× 154 1.4× 79 0.9× 98 1.6× 29 0.5× 30 502
Jiawen Huang China 5 243 1.1× 310 2.8× 104 1.2× 28 0.5× 51 1.0× 10 863
Akinori Yamauchi Japan 10 92 0.4× 103 0.9× 17 0.2× 11 0.2× 23 0.4× 25 343
Karthickeyan Chella Krishnan United States 15 114 0.5× 321 2.9× 54 0.6× 21 0.3× 84 1.6× 25 775

Countries citing papers authored by Ming-Yi Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Yi Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming-Yi Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Yi Zhou. A scholar is included among the top collaborators of Ming-Yi 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 Ming-Yi Zhou. Ming-Yi 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.
Gregory, Devon A., Mónica Trujillo, Clayton Rushford, et al.. (2022). Genetic diversity and evolutionary convergence of cryptic SARS- CoV-2 lineages detected via wastewater sequencing. PLoS Pathogens. 18(10). e1010636–e1010636. 37 indexed citations
2.
Wang, Danbo, Cuishan Guo, Yan Li, et al.. (2021). Oestrogen up-regulates DNMT1 and leads to the hypermethylation of RUNX3 in the malignant transformation of ovarian endometriosis. Reproductive BioMedicine Online. 44(1). 27–37. 18 indexed citations
3.
4.
5.
Zhou, Ming-Yi, et al.. (2018). Neutrophil-to-Lymphocyte Ratio and Platelet Count Predict Long-Term Outcome of Stage IIIC Epithelial Ovarian Cancer. Cellular Physiology and Biochemistry. 46(1). 178–186. 22 indexed citations
6.
Zhou, Ming-Yi, et al.. (2017). Neuron-specific enolase and response to initial therapy are important prognostic factors in patients with small cell lung cancer. Clinical & Translational Oncology. 19(7). 865–873. 23 indexed citations
7.
Zhou, Ming-Yi, Ping Yu, Jinglei Qu, et al.. (2016). Efficacy of Bevacizumab in the First-Line Treatment of Patients with RAS Mutations Metastatic Colorectal Cancer: a Systematic Review and Network Meta-Analysis. Cellular Physiology and Biochemistry. 40(1-2). 361–369. 23 indexed citations
8.
Zhou, Ming-Yi, et al.. (2010). Antioxidative and anti-inflammatory properties of Citrus sulcata extracts. Food Chemistry. 124(3). 958–963. 46 indexed citations
9.
Golshayan, Ali, S. George, D.Y.C. Heng, et al.. (2008). Metastatic renal cell carcinoma (mRCC) patients (pts) with sarcomatoid features treated with VEGF-targeted therapy. Journal of Clinical Oncology. 26(15_suppl). 5102–5102. 3 indexed citations
10.
Zhou, Ming-Yi, et al.. (2003). Interferon-inducible genes in the rat adrenal gland and vascular smooth muscle cells. Molecular and Cellular Endocrinology. 200(1-2). 81–87. 3 indexed citations
11.
Zhou, Ming-Yi, et al.. (2001). Angiotensin stimulates the expression of interferon-inducible genes in H295R cells. Molecular and Cellular Endocrinology. 176(1-2). 21–27. 5 indexed citations
12.
Zhou, Ming-Yi, et al.. (2000). An alternatively spliced rat mineralocorticoid receptor mRNA causing truncation of the steroid binding domain. Molecular and Cellular Endocrinology. 159(1-2). 125–131. 33 indexed citations
13.
Romero, Damián G., Ming-Yi Zhou, & Celso E. Gómez-Sánchez. (2000). Cloning and expression of the bovine 11β-hydroxysteroid dehydrogenase type-2. The Journal of Steroid Biochemistry and Molecular Biology. 72(5). 231–237. 13 indexed citations
14.
Morita, Hiroyuki, Eduardo N. Cozza, Ming-Yi Zhou, et al.. (1997). Regulation of the 11β-hydroxysteroid dehydrogenase in the rat adrenal. Endocrine. 7(3). 331–335. 16 indexed citations
15.
Zhou, Ming-Yi, María del C. Vila, Elise P. Gómez-Sánchez, & Celso E. Gómez-Sánchez. (1997). Cloning of two alternatively spliced 21-hydroxylase CDNAs from rat adrenal. The Journal of Steroid Biochemistry and Molecular Biology. 62(4). 277–286. 9 indexed citations
16.
Gómez-Sánchez, Elise P., et al.. (1997). The sheep kidney contains a novel unidirectional, high affinity NADP+-dependent 11β-hydroxysteroid dehydrogenase (11β-HSD-3). Steroids. 62(5). 444–450. 38 indexed citations
17.
Morita, Hiroyuki, Ming-Yi Zhou, Mark F. Foecking, et al.. (1996). 11 beta-Hydroxysteroid dehydrogenase type 2 complementary deoxyribonucleic acid stably transfected into Chinese hamster ovary cells: specific inhibition by 11 alpha-hydroxyprogesterone.. Endocrinology. 137(6). 2308–2314. 37 indexed citations
18.
Gómez-Sánchez, Elise P., Ming-Yi Zhou, & Celso E. Gómez-Sánchez. (1996). Mineralocorticoids, salt and high blood pressure. Steroids. 61(4). 184–188. 55 indexed citations
19.
Zhou, Ming-Yi, et al.. (1995). Stable expression of rat cytochrome P450 11β-Hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) in MA-10 cells. The Journal of Steroid Biochemistry and Molecular Biology. 52(6). 523–528. 13 indexed citations
20.

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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