Cai Li

3.2k citations
59 papers · 2.4k indexed · 1 hit paper · h-index 15
Topics
Statistical Methods and Inference (7 papers)Head and Neck Cancer Studies (5 papers)Bayesian Methods and Mixture Models (4 papers)

In The Last Decade

Cai Li

51 papers receiving 2.4k citations

Hit Papers

Synaptotagmin I: A major Ca2+ sensor for transmitter rele...199420262004201519942505007501000

Peers

Cai Li
Comparison fields: 5 of 140
  • Molecular Biology 1.4k
  • Cell Biology 1.4k
  • Cellular and Molecular Neuroscience 734
  • Physiology 300
  • Surgery 261
Replace Juan Rong with:
Juan Rong United States
Caroline Dart United Kingdom
Chadwick M. Hales United States
Stéphanie Baulac France
Juris Galvanovskis Sweden
Bing Zhou China
Madan M. Kwatra United States
Kinga Szigeti United States
Jeffrey J. Saucerman United States
Cai Li relative to Juan Rong United States Juan Rong's profile →
Citations per field
00.5×3.9×
Juan Rong · 1×
Citations per year

Countries citing papers authored by Cai Li

Since Specialization
Citations

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

Fields of papers citing papers by Cai Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cai Li

This figure shows the co-authorship network connecting the top 25 collaborators of Cai Li. A scholar is included among the top collaborators of Cai Li 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 Cai Li. Cai Li 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
#WorkIndexed citations
1 1
2 0
3 1
4 1
5 1
6 3
7 1
8 2
9 2
10 42
11 62
12 9
13 42
14
Fermion Representation of Quantum Toroidal Algebra
1
15 4
16 12
17 6
18 199
19 170
20
Synaptotagmin I: A major Ca2+ sensor for transmitter release at a central synapsebreakdown →
1196

About Cai Li

Cai Li is a scholar working on Computational Mathematics, Otorhinolaryngology and Statistics and Probability, having authored 59 papers that have together received 2.4k indexed citations. Recurring topics across this work include Statistical Methods and Inference (7 papers), Head and Neck Cancer Studies (5 papers) and Bayesian Methods and Mixture Models (4 papers). The work is most often cited by research in Cell Biology (1.4k citations), Cellular and Molecular Neuroscience (734 citations) and Physiology (177 citations). Cai Li has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Thomas C. Südhof, Martin Geppert, Thomas W. Rosahl, Robert E. Hammer, Charles F. Stevens, Yukiko Goda, Reinhard Jahn, Sheng Luo, Thomas C. Südhof and Bernd Stahl. Their work appears in journals such as Cell, Neuron and Journal of Clinical Oncology.

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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