Ming Bai

23 papers receiving 381 citations

Peers

Ming Bai
Comparison fields: 5 of 72
  • Nephrology 80
  • Endocrine and Autonomic Systems 31
  • Aquatic Science 31
  • Nutrition and Dietetics 42
  • Sensory Systems 12
Replace Bernadette Wallendorff with:
Bernadette Wallendorff Canada
Madhumitha Rajagopal United States
Goichi Ogimoto Japan
Gustavo Ares United States
Jesse W. Bowen United States
Beth Zavilowitz United States
Anja Krabbenhöft Germany
M. Tosco Italy
Yurena Vivas Spain
C. Khadouri France
Ming Bai relative to Bernadette Wallendorff Canada Bernadette Wallendorff's profile →
Citations per field
00.5×3.3×
Bernadette Wallendorff · 1×
Citations per year

Countries citing papers authored by Ming Bai

Since Specialization
Citations

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

Fields of papers citing papers by Ming Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming Bai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ming Bai Line = papers co-authored together Ming Bai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002106
2 202259
3 199656
4 199840
5 201631
6 202118
7 202316
8
Gemcitabine sensitivity factors, hENT1 and RRM1 as potential prognostic biomarker for advanced biliary tract cancer.
201413
9 200313
10 20187
11 20245
12 20255
13 20234
14 20222
15 20222
16 20241
17
Global Existence and Uniqueness for a Nonlinear Cell Population Model with Age Structure
20101
18 20231
19
Optimization of Separation and Purification of Total Flavonoids from the Pine Pollen by Macroporous Resin
20091
20 20211

About Ming Bai

Ming Bai is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Nephrology, Physiology and Pharmacology, having authored 26 papers that have together received 385 indexed citations. Recurring topics across this work include Gastric Cancer Management and Outcomes (3 papers), Magnesium in Health and Disease (2 papers), Physiological and biochemical adaptations (2 papers), Parathyroid Disorders and Treatments (2 papers), Cardiac Imaging and Diagnostics (1 paper), Alzheimer's disease research and treatments (1 paper), Fish biology, ecology, and behavior (1 paper) and Ion Transport and Channel Regulation (1 paper). The work is most often cited by research in Nephrology (80 citations), Endocrine and Autonomic Systems (31 citations), Aquatic Science (31 citations), Nutrition and Dietetics (42 citations) and Sensory Systems (12 citations). Ming Bai has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Michelle A. Baum, Steven Hébert, Edward M. Brown, H. William Harris, S. J. Quinn, Marlies Elger, H. Hentschel, Naibedya Chattopadhyay, Daniela Riccardi and Merlin Crossley. Their work appears in journals such as BMC Cardiovascular Disorders, Journal of Clinical Oncology, BMC Cancer, Cancer Immunology Immunotherapy and Proceedings of the National Academy of Sciences.

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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