Si-Qi Liu

1.6k citations
24 papers · 1.1k · h-index 15

Impact in

Papers in

Si-Qi Liu

23 papers receiving 1.1k citations

Peers

Si-Qi Liu
Comparison fields: 5 of 92
  • Developmental Neuroscience 73
  • Biochemistry 119
  • Pathology and Forensic Medicine 255
  • Cancer Research 167
  • Cell Biology 148
Replace Jean C. Bopassa with:
Jean C. Bopassa United States
Hiran A. Prag United Kingdom
Nancy F. Roeser United States
Hartmut Lüss Germany
Chuanlin Wang China
Xiyuan Lu United States
Ryan P. Taylor United States
Cathal P. Connern United Kingdom
Nicole Avéret France
Si-Qi Liu relative to Jean C. Bopassa United States Jean C. Bopassa's profile →
Citations per field
00.5×4.3×
Jean C. Bopassa · 1×
Citations per year

Countries citing papers authored by Si-Qi Liu

Since Specialization
Citations

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

Fields of papers citing papers by Si-Qi Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000310
2 2006123
3 2014120
4 2002107
5 200079
6 201448
7 201647
8 201447
9 200137
10 201728
11 202322
12 199321
13 200316
14 201615
15 202115
16 202411
17 20239
18 20244
19 20243
20 20233

About Si-Qi Liu

Si-Qi Liu is a scholar working on Molecular Biology, Cell Biology, Immunology, Pathology and Forensic Medicine and Physiology, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Aldose Reductase and Taurine (5 papers), Plant Molecular Biology Research (3 papers), MicroRNA in disease regulation (3 papers), Heme Oxygenase-1 and Carbon Monoxide (3 papers), Immune Cell Function and Interaction (3 papers), Alcohol Consumption and Health Effects (2 papers), Plant nutrient uptake and metabolism (2 papers) and Marine and coastal ecosystems (2 papers). The work is most often cited by research in Developmental Neuroscience (73 citations), Biochemistry (119 citations), Pathology and Forensic Medicine (255 citations), Cancer Research (167 citations) and Cell Biology (148 citations). Si-Qi Liu has collaborated with scholars based in China, United States and United Arab Emirates. Frequent co-authors include Aruni Bhatnagar, Yu-Ting Xuan, Roberto Bolli, Ken Shinmura, Xian‐Liang Tang, Shan Jiang, Qi-Jing Li, Yang Wang, Hitoshi Takano and Chaoran Li. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Science of The Total Environment, Redox Biology, FEBS Letters and Molecular & Cellular Proteomics.

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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