Fēi Li

6.1k citations
229 papers · 4.1k · h-index 31

Impact in

Papers in

Fēi Li

214 papers receiving 4.0k citations

Peers

Fēi Li
Comparison fields: 5 of 175
  • Biological Psychiatry 93
  • Periodontics 147
  • Cellular and Molecular Neuroscience 566
  • Modeling and Simulation 116
  • Cognitive Neuroscience 449
Replace Omar F. Khabour with:
Omar F. Khabour Jordan
Aletta D. Kraneveld Netherlands
Matthew B. McQueen United States
Francesco Chiappelli United States
Raymond Chuen‐Chung Chang Hong Kong
Maurizio Simmaco Italy
Daniel L. Smith United States
Kathryn Sandberg United States
Brian J. Eastwood United Kingdom
Aurelia Santoro Italy
Fēi Li relative to Omar F. Khabour Jordan Omar F. Khabour's profile →
Citations per field
00.5×3.5×
Omar F. Khabour · 1×
Citations per year

Countries citing papers authored by Fēi Li

Since Specialization
Citations

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

Fields of papers citing papers by Fēi Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 229 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009271
2 2019221
3 2006212
4 2020135
5 201198
6 201398
7 201084
8 201183
9 200380
10 200675
11 201866
12 202057
13 201457
14 201757
15 201057
16 201557
17 201551
18 201845
19 201541
20 202241

About Fēi Li

Fēi Li is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Cognitive Neuroscience, Public Health, Environmental and Occupational Health and Genetics, having authored 229 papers that have together received 4.1k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (30 papers), Memory and Neural Mechanisms (13 papers), Gestational Diabetes Research and Management (11 papers), Receptor Mechanisms and Signaling (10 papers), Autism Spectrum Disorder Research (10 papers), Neurotransmitter Receptor Influence on Behavior (9 papers), Genomic variations and chromosomal abnormalities (8 papers) and Neuroscience and Neural Engineering (8 papers). The work is most often cited by research in Biological Psychiatry (93 citations), Periodontics (147 citations), Cellular and Molecular Neuroscience (566 citations), Modeling and Simulation (116 citations) and Cognitive Neuroscience (449 citations). Fēi Li has collaborated with scholars based in China, United States and Denmark. Frequent co-authors include Joe Z. Tsien, Mingyu Xu, Xuefeng Xu, Jijun Li, Xinzhu Meng, Jun Zhang, Viktor R. Drel, Irina G. Obrosova, Xiaoming Shen and Jeho Shin. Their work appears in journals such as PLoS ONE, Scientific Reports, BMC Public Health, Molecular Psychiatry and Frontiers in Endocrinology.

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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