Ping Luan

44 papers receiving 1.0k citations

Peers

Ping Luan
Comparison fields: 5 of 125
  • Neurology 86
  • Biomaterials 111
  • Physiology 150
  • Developmental Neuroscience 22
  • Animal Science and Zoology 58
Replace Zhiyong He with:
Zhiyong He China
Bernard Fioretti Italy
Federico Sesti United States
Huiling Gao China
Jing Ji China
Vincenzo Giuseppe Nicoletti Italy
Maoping Tang United States
Gildas Loussouarn France
Sandra Rebelo Portugal
Ping Luan relative to Zhiyong He China Zhiyong He's profile →
Citations per field
00.5×2.8×
Zhiyong He · 1×
Citations per year

Countries citing papers authored by Ping Luan

Since Specialization
Citations

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

Fields of papers citing papers by Ping Luan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016153
2 201298
3 202189
4 201558
5 201554
6 201751
7 201738
8 201734
9 202333
10 202231
11 201531
12 202124
13 201523
14
Neurotropin reduces memory impairment and neuroinflammation via BDNF/NF-κB in a transgenic mouse model of Alzheimer's disease.
201923
15 202323
16 202121
17 201518
18 202217
19
Tyrosine Hydroxylase as a Target for Deltamethrin in the Nigrostriatal Dopaminergic Pathway
200615
20 201815

About Ping Luan

Ping Luan is a scholar working on Molecular Biology, Biomedical Engineering, Materials Chemistry, Cellular and Molecular Neuroscience and Physiology, having authored 46 papers that have together received 1.0k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (5 papers), Alzheimer's disease research and treatments (5 papers), Nanocluster Synthesis and Applications (5 papers), Animal Nutrition and Physiology (4 papers), Genetic and phenotypic traits in livestock (3 papers), EEG and Brain-Computer Interfaces (3 papers), Nanoparticle-Based Drug Delivery (3 papers) and Neurological Disease Mechanisms and Treatments (3 papers). The work is most often cited by research in Neurology (86 citations), Biomaterials (111 citations), Physiology (150 citations), Developmental Neuroscience (22 citations) and Animal Science and Zoology (58 citations). Ping Luan has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Beibei Gu, Songhua Xiao, Wang Liao, Jun Liu, Shengnuo Fan, Wenli Fang, Enxiang Tao, Jun Liu, Lianhong Yang and Nansha Gao. Their work appears in journals such as CNS Neuroscience & Therapeutics, animal, Chinese Chemical Letters, Ageing Research Reviews and Drug Delivery.

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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