Ming-Ming Tsai

1.8k total citations
41 papers, 1.4k citations indexed

About

Ming-Ming Tsai is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Ming-Ming Tsai has authored 41 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 14 papers in Cancer Research and 8 papers in Oncology. Recurrent topics in Ming-Ming Tsai's work include Cancer-related molecular mechanisms research (7 papers), MicroRNA in disease regulation (5 papers) and Growth Hormone and Insulin-like Growth Factors (5 papers). Ming-Ming Tsai is often cited by papers focused on Cancer-related molecular mechanisms research (7 papers), MicroRNA in disease regulation (5 papers) and Growth Hormone and Insulin-like Growth Factors (5 papers). Ming-Ming Tsai collaborates with scholars based in Taiwan, United States and India. Ming-Ming Tsai's co-authors include Kwang‐Huei Lin, Chung‐Ying Tsai, Hsiang‐Cheng Chi, Chia‐Siu Wang, Chau‐Ting Yeh, Hsi‐Lung Hsieh, Ya‐Hui Huang, Yang-Hsiang Lin, Yi‐Hsin Tseng and I‐Hsiao Chung and has published in prestigious journals such as PLoS ONE, Hepatology and Oncogene.

In The Last Decade

Ming-Ming Tsai

41 papers receiving 1.4k 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-Ming Tsai Taiwan 24 796 558 299 166 146 41 1.4k
Zheng Liu China 25 983 1.2× 448 0.8× 423 1.4× 76 0.5× 122 0.8× 75 1.6k
Yuanyuan Weng China 20 677 0.9× 297 0.5× 200 0.7× 105 0.6× 162 1.1× 30 1.2k
Yinxue Yang China 23 948 1.2× 379 0.7× 259 0.9× 65 0.4× 115 0.8× 44 1.5k
Adriane Feijó Evangelista Brazil 22 834 1.0× 622 1.1× 265 0.9× 57 0.3× 148 1.0× 75 1.4k
Lihong Chen China 20 1.1k 1.4× 297 0.5× 478 1.6× 95 0.6× 123 0.8× 50 1.7k
Rishi Raj Chhipa United States 17 837 1.1× 347 0.6× 239 0.8× 170 1.0× 61 0.4× 20 1.3k
Sung Hoo Jung South Korea 24 772 1.0× 310 0.6× 392 1.3× 89 0.5× 104 0.7× 86 1.5k
Kiyomu Fujii Japan 28 888 1.1× 421 0.8× 380 1.3× 116 0.7× 221 1.5× 75 1.9k
Sonja M. Kessler Germany 22 630 0.8× 465 0.8× 132 0.4× 105 0.6× 115 0.8× 41 1.1k
Shu‐Wing Ng United States 22 1.1k 1.4× 698 1.3× 250 0.8× 101 0.6× 378 2.6× 41 2.2k

Countries citing papers authored by Ming-Ming Tsai

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Ming Tsai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming-Ming Tsai

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Ming Tsai. A scholar is included among the top collaborators of Ming-Ming Tsai 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-Ming Tsai. Ming-Ming Tsai 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.
Lee, Tsong‐Hai, Jiun-Liang Chen, Ming-Ming Tsai, et al.. (2023). Protective Effects of Sophoraflavanone G by Inhibiting TNF-α-Induced MMP-9-Mediated Events in Brain Microvascular Endothelial Cells. International Journal of Molecular Sciences. 25(1). 283–283. 5 indexed citations
2.
Wang, Ling‐Yu, Yiwen Wang, Ming-Ming Tsai, et al.. (2023). Evaluation and Application of Drug Resistance by Biomarkers in the Clinical Treatment of Liver Cancer. Cells. 12(6). 869–869. 14 indexed citations
3.
Hsieh, Hsi‐Lung, et al.. (2022). Molecular mechanism of therapeutic approaches for human gastric cancer stem cells. World Journal of Stem Cells. 14(1). 76–91. 19 indexed citations
5.
Lee, Tsong‐Hai, Jiun-Liang Chen, Pei‐Shan Liu, et al.. (2020). Rottlerin, a natural polyphenol compound, inhibits upregulation of matrix metalloproteinase-9 and brain astrocytic migration by reducing PKC-δ-dependent ROS signal. Journal of Neuroinflammation. 17(1). 177–177. 23 indexed citations
6.
Chi, Hsiang‐Cheng, Chung‐Ying Tsai, Ming-Ming Tsai, Chau‐Ting Yeh, & Kwang‐Huei Lin. (2019). Molecular functions and clinical impact of thyroid hormone-triggered autophagy in liver-related diseases. Journal of Biomedical Science. 26(1). 24–24. 73 indexed citations
7.
Lin, Yang-Hsiang, Meng‐Han Wu, Chia‐Jung Liao, et al.. (2015). Repression of microRNA-130b by thyroid hormone enhances cell motility. Journal of Hepatology. 62(6). 1328–1340. 47 indexed citations
8.
Tsai, Chung‐Ying, Chia‐Siu Wang, Ming-Ming Tsai, et al.. (2014). Interleukin-32 Increases Human Gastric Cancer Cell Invasion Associated with Tumor Progression and Metastasis. Clinical Cancer Research. 20(9). 2276–2288. 92 indexed citations
9.
Tsai, Ming-Ming, Chia‐Siu Wang, Chung‐Ying Tsai, et al.. (2014). MicroRNA-196a/-196b promote cell metastasis via negative regulation of radixin in human gastric cancer. Cancer Letters. 351(2). 222–231. 71 indexed citations
10.
Chen, Cheng‐Yi, I‐Hsiao Chung, Ming-Ming Tsai, et al.. (2014). Thyroid hormone enhanced human hepatoma cell motility involves brain-specific serine protease 4 activation via ERK signaling. Molecular Cancer. 13(1). 162–162. 27 indexed citations
11.
Liao, Chia‐Jung, et al.. (2012). Thyroid hormone receptors promote metastasis of human hepatoma cells via regulation of TRAIL. Cell Death and Differentiation. 19(11). 1802–1814. 29 indexed citations
12.
Cheng, Wanli, Ming-Ming Tsai, Chung‐Ying Tsai, et al.. (2012). Correction: Glyoxalase-I Is a Novel Prognosis Factor Associated with Gastric Cancer Progression. PLoS ONE. 7(9). 18 indexed citations
13.
Cheng, Wanli, Ming-Ming Tsai, Chung‐Ying Tsai, et al.. (2012). Glyoxalase-I Is a Novel Prognosis Factor Associated with Gastric Cancer Progression. PLoS ONE. 7(3). e34352–e34352. 45 indexed citations
14.
Huang, Ya‐Hui, et al.. (2011). Overexpression of CXCL1 and its receptor CXCR2 promote tumor invasion in gastric cancer. Annals of Oncology. 22(10). 2267–2276. 108 indexed citations
15.
Chen, Cheng‐Yi, Lang‐Ming Chi, Hsiang‐Cheng Chi, et al.. (2011). Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC)-based Quantitative Proteomics Study of a Thyroid Hormone-regulated Secretome in Human Hepatoma Cells. Molecular & Cellular Proteomics. 11(4). M111.011270–M111.011270. 37 indexed citations
16.
Yeh, Chau‐Ting, Ya‐Hui Huang, Hsiang‐Cheng Chi, et al.. (2011). Dickkopf 4 positively regulated by the thyroid hormone receptor suppresses cell invasion in human hepatoma cells. Hepatology. 55(3). 910–920. 59 indexed citations
17.
Liao, Chia‐Jung, Tzu-I Wu, Ya‐Hui Huang, et al.. (2010). Overexpression of gelsolin in human cervical carcinoma and its clinicopathological significance. Gynecologic Oncology. 120(1). 135–144. 38 indexed citations
18.
Huang, Ya-Hui, et al.. (2009). Regulation of AKR1B1 by thyroid hormone and its receptors. Molecular and Cellular Endocrinology. 307(1-2). 109–117. 21 indexed citations
19.
Doong, Shin-Lian, et al.. (1998). Transactivation of the human MDR1 gene by hepatitis B virus X gene product. Journal of Hepatology. 29(6). 872–878. 11 indexed citations
20.
Hwang, Tsann‐Long, Ying‐Tung Lau, Ming-Ming Tsai, & Maw-Shung Liu. (1997). Changes of adenosine triphosphate-dependent calcium uptake in microsomal fractions of rat liver during sepsis. Surgery. 121(6). 662–667. 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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