Wei Tan

2.6k citations
118 papers · 1.6k · h-index 21

Impact in

Papers in

Wei Tan

116 papers receiving 1.6k citations

Peers

Wei Tan
Comparison fields: 5 of 146
  • Statistics and Probability 299
  • Modeling and Simulation 111
  • Virology 60
  • Anesthesiology and Pain Medicine 60
  • Molecular Biology 616
Replace Beat Neuenschwander with:
Beat Neuenschwander Switzerland
Ramy Arnaout United States
Estelle Kuhn France
Michael J. Chappell United Kingdom
Joseph E. Lucas United States
Adrian Dobra United States
Knut M. Wittkowski United States
Neil D. Evans United Kingdom
Momiao Xiong United States
Jorge L. Sepulveda United States
Wei Tan relative to Beat Neuenschwander Switzerland Beat Neuenschwander's profile →
Citations per field
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Citations per year

Countries citing papers authored by Wei Tan

Since Specialization
Citations

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

Fields of papers citing papers by Wei Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Wei Tan, 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 Wei Tan Line = papers co-authored together Wei Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 118 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007117
2 1999110
3 200095
4 198884
5 199858
6 200258
7 199558
8 200547
9 198547
10 198646
11 199743
12 198942
13 201335
14 198333
15 201730
16 202329
17 198226
18 199626
19 202126
20 202124

About Wei Tan

Wei Tan is a scholar working on Statistics and Probability, Pulmonary and Respiratory Medicine, Molecular Biology, Genetics and Epidemiology, having authored 118 papers that have together received 1.6k indexed citations. Recurring topics across this work include Respiratory Support and Mechanisms (20 papers), Advanced Statistical Methods and Models (17 papers), Bayesian Methods and Mixture Models (12 papers), Statistical Distribution Estimation and Applications (12 papers), RNA Research and Splicing (9 papers), Airway Management and Intubation Techniques (8 papers), Genetic Mapping and Diversity in Plants and Animals (8 papers) and Genetics and Plant Breeding (8 papers). The work is most often cited by research in Statistics and Probability (299 citations), Modeling and Simulation (111 citations), Virology (60 citations), Anesthesiology and Pain Medicine (60 citations) and Molecular Biology (616 citations). Wei Tan has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Stefan Schwartz, Jenifer Bear, Barbara K. Felber, Andrei S. Zolotukhin, Marcus Sokolowski, Bing Dai, Steven Piantadosi, Mitchell H. Gail, Hongwen Zhao and Mohammad Tabatabai. Their work appears in journals such as Mathematical and Computer Modelling, Biometrical Journal, Journal of Statistical Computation and Simulation, Therapeutic Advances in Respiratory Disease and Biometrics.

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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