Lan Wang

2.3k citations
73 papers · 1.4k · h-index 19

Impact in

Papers in

Lan Wang

64 papers receiving 1.3k citations

Peers

Lan Wang
Comparison fields: 5 of 149
  • Statistics and Probability 265
  • Infectious Diseases 370
  • Virology 65
  • Epidemiology 268
  • Modeling and Simulation 37
Replace Ying Qing Chen with:
Ying Qing Chen United States
Yangxin Huang United States
Kung‐Jong Lui United States
Ekkehart Dietz Germany
Anne M. Presanis United Kingdom
Steve Bennett United Kingdom
Els Goetghebeur Belgium
Pardeep Khanna India
Henry Mwambi South Africa
Zonghui Hu United States
Lan Wang relative to Ying Qing Chen United States Ying Qing Chen's profile →
Citations per field
00.5×1.5×2.3×
Ying Qing Chen · 1×
Citations per year

Countries citing papers authored by Lan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Lan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013223
2 2012215
3 200790
4 201754
5 202053
6 201444
7 202344
8 201742
9 201139
10 201436
11 202335
12 201132
13 202025
14 201724
15 202122
16 201420
17 202120
18 200919
19 201919
20 202217

About Lan Wang

Lan Wang is a scholar working on Public Health, Environmental and Occupational Health, Epidemiology, Molecular Biology, Infectious Diseases and Statistics and Probability, having authored 73 papers that have together received 1.4k indexed citations. Recurring topics across this work include Statistical Methods and Inference (7 papers), Respiratory viral infections research (4 papers), Maternal Mental Health During Pregnancy and Postpartum (3 papers), Gut microbiota and health (3 papers), Hepatitis C virus research (3 papers), Innovation and Knowledge Management (3 papers), HIV, Drug Use, Sexual Risk (3 papers) and Bayesian Methods and Mixture Models (3 papers). The work is most often cited by research in Statistics and Probability (265 citations), Infectious Diseases (370 citations), Virology (65 citations), Epidemiology (268 citations) and Modeling and Simulation (37 citations). Lan Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yichao Wu, Runze Li, Wei Guo, Lu Wang, Ning Wang, Dongmin Li, Yan Cui, Zunyou Wu, Ning Wang and Xiaoshan Li. Their work appears in journals such as Journal of the American Statistical Association, PLoS ONE, Bioresources and Bioprocessing, Molecular and Cellular Biochemistry and Blood.

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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