Ming Bai

537 total citations
25 papers, 374 citations indexed

About

Ming Bai is a scholar working on Pulmonary and Respiratory Medicine, Surgery and Oncology. According to data from OpenAlex, Ming Bai has authored 25 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Pulmonary and Respiratory Medicine, 8 papers in Surgery and 5 papers in Oncology. Recurrent topics in Ming Bai's work include Gastric Cancer Management and Outcomes (6 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers) and Gastrointestinal Tumor Research and Treatment (4 papers). Ming Bai is often cited by papers focused on Gastric Cancer Management and Outcomes (6 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers) and Gastrointestinal Tumor Research and Treatment (4 papers). Ming Bai collaborates with scholars based in China, United States and Greece. Ming Bai's co-authors include Edward M. Brown, Steven Hébert, H. William Harris, Michelle A. Baum, Marlies Elger, S. J. Quinn, H. Hentschel, Daniela Riccardi, Naibedya Chattopadhyay and Leigh Delbridge and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Journal of Clinical Oncology.

In The Last Decade

Ming Bai

24 papers receiving 368 citations

Peers

Ming Bai
Comparison fields: 5 of 73
  • Molecular Biology 146
  • Nephrology 85
  • Surgery 66
  • Pulmonary and Respiratory Medicine 57
  • Oncology 54
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Yurena Vivas Spain View profile →
Citations per field, relative to Ming Bai
Ming Bai · 1×
Citations per year, relative to Ming Bai
Ming Bai · 1×

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-authorship network of co-authors of Ming Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Bai. A scholar is included among the top collaborators of Ming Bai 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 Bai. Ming Bai 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
# Work Indexed citations
1 0
2 1
3 3
4 1
5 3
6 1
7 14
8 2
9 50
10 2
11 1
12 17
13 7
14 31
15
Gemcitabine sensitivity factors, hENT1 and RRM1 as potential prognostic biomarker for advanced biliary tract cancer.
13
16
Global Existence and Uniqueness for a Nonlinear Cell Population Model with Age Structure
1
17
Optimization of Separation and Purification of Total Flavonoids from the Pine Pollen by Macroporous Resin
1
18 105
19 40
20 56

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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