Xiaohan Wang

3k citations
111 papers · 2.3k · h-index 29

Impact in

Papers in

Xiaohan Wang

104 papers receiving 2.3k citations

Peers

Xiaohan Wang
Comparison fields: 5 of 138
  • Pharmacology 444
  • Endocrine and Autonomic Systems 149
  • Cellular and Molecular Neuroscience 176
  • Sensory Systems 57
  • Neurology 82
Replace Cristina Lanni with:
Cristina Lanni Italy
Ting Zhang China
Hong Qing China
Satoshi Imai Japan
Wenjun Li China
Chong V. Li China
Xiuli Dan Hong Kong
William R. Mundy United States
Maria Camila Almeida Brazil
Xiaohan Wang relative to Cristina Lanni Italy Cristina Lanni's profile →
Citations per field
00.5×2×4×6×8×9.5×
Cristina Lanni · 1×
Citations per year

Countries citing papers authored by Xiaohan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996160
2 2018103
3 201789
4 201587
5 201186
6 201778
7 201774
8 202372
9 202365
10 201364
11 201461
12 201461
13 201553
14 202351
15 202347
16 201343
17 201643
18 201342
19 201742
20 202242

About Xiaohan Wang

Xiaohan Wang is a scholar working on Pharmacology, Endocrine and Autonomic Systems, Industrial and Manufacturing Engineering, Cellular and Molecular Neuroscience and Neurology, having authored 111 papers that have together received 2.3k indexed citations. Recurring topics across this work include Microbial Natural Products and Biosynthesis (11 papers), Circadian rhythm and melatonin (6 papers), Neuroscience and Neuropharmacology Research (5 papers), Ion channel regulation and function (5 papers), Maritime Ports and Logistics (5 papers), Cannabis and Cannabinoid Research (4 papers), Reliability and Maintenance Optimization (3 papers) and Hearing, Cochlea, Tinnitus, Genetics (3 papers). The work is most often cited by research in Pharmacology (444 citations), Endocrine and Autonomic Systems (149 citations), Cellular and Molecular Neuroscience (176 citations), Sensory Systems (57 citations) and Neurology (82 citations). Xiaohan Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ligang Zhou, Daowan Lai, Peter Zafian, Roger J. Colbran, Weibo Sun, Xiaoxiang Fu, Jiajia Meng, Jin Tian, Xiao Yang Gong and Ali Wang. Their work appears in journals such as Molecules, Journal of Neuroscience, Proceedings of the National Academy of Sciences, Nature and Food Research International.

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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