Xiaodan Liu

1.4k citations
34 papers · 972 · h-index 14

Impact in

Papers in

Xiaodan Liu

32 papers receiving 964 citations

Peers

Xiaodan Liu
Comparison fields: 5 of 91
  • Physiology 340
  • Cellular and Molecular Neuroscience 218
  • Neurology 82
  • Sensory Systems 36
  • Neurology 96
Replace Ikuko Suzuki with:
Ikuko Suzuki Japan
Katherine Hamel United States
Jiu Lin China
Alexander J. Davies United Kingdom
Adrienn Markovics Hungary
Martina Kurejová Germany
Kenzo Tsuzuki Japan
Chen Zhang China
Travis P. Barr United States
Ming-Dong Zhang Sweden
Xiaodan Liu relative to Ikuko Suzuki Japan Ikuko Suzuki's profile →
Citations per field
00.5×6.7×
Ikuko Suzuki · 1×
Citations per year

Countries citing papers authored by Xiaodan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015164
2 2015145
3 2010136
4 202188
5 201964
6 201455
7 202240
8 202038
9 201638
10 201436
11 201934
12 201827
13 201527
14 201817
15 202213
16 202112
17 20248
18 20204
19
[Expression of CXCL16/CXCR6 in fibroblast-like synoviocytes in rheumatoid arthritis and its role in synoviocyte proliferation].
20174
20 20203

About Xiaodan Liu

Xiaodan Liu is a scholar working on Physiology, Cellular and Molecular Neuroscience, Molecular Biology, Rheumatology and Oncology, having authored 34 papers that have together received 972 indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (7 papers), Nerve injury and regeneration (4 papers), Systemic Lupus Erythematosus Research (3 papers), Cancer Cells and Metastasis (2 papers), Salivary Gland Disorders and Functions (2 papers), Oral Health Pathology and Treatment (2 papers), Mesenchymal stem cell research (2 papers) and Genetic Neurodegenerative Diseases (2 papers). The work is most often cited by research in Physiology (340 citations), Cellular and Molecular Neuroscience (218 citations), Neurology (82 citations), Sensory Systems (36 citations) and Neurology (96 citations). Xiaodan Liu has collaborated with scholars based in China and United States. Frequent co-authors include Guo‐Gang Xing, Jie Cai, Ji‐Sheng Han, Dong Fang, You Wan, Xu Ding, Song Li, Lingyu Kong, Zongran Liu and Jing Zhang. Their work appears in journals such as Journal of Chromatography A, Biomedicine & Pharmacotherapy, iScience, Developmental Cell and Glia.

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.

Explore authors with similar magnitude of impact