Feisi Liang

498 total citations
6 papers, 372 citations indexed

About

Feisi Liang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Geriatrics and Gerontology. According to data from OpenAlex, Feisi Liang has authored 6 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 2 papers in Geriatrics and Gerontology. Recurrent topics in Feisi Liang's work include PI3K/AKT/mTOR signaling in cancer (3 papers), Nerve injury and regeneration (2 papers) and Sirtuins and Resveratrol in Medicine (2 papers). Feisi Liang is often cited by papers focused on PI3K/AKT/mTOR signaling in cancer (3 papers), Nerve injury and regeneration (2 papers) and Sirtuins and Resveratrol in Medicine (2 papers). Feisi Liang collaborates with scholars based in United States, United Kingdom and China. Feisi Liang's co-authors include Yang Hu, Haoliang Huang, Linqing Miao, Yang Liu, Xiuyin Teng, Shaohua Li, Chen Ling, Qizhao Wang, Michael E. Selzer and Lin Xu and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and eLife.

In The Last Decade

Feisi Liang

5 papers receiving 371 citations

Peers

Feisi Liang
Comparison fields: 5 of 60
  • Molecular Biology 238
  • Cellular and Molecular Neuroscience 154
  • Cell Biology 80
  • Ophthalmology 62
  • Developmental Neuroscience 61
Replace Philippe M. D’Onofrio with:
Philippe M. D’Onofrio Canada
Jason Charish Canada
Vinícius Toledo Ribas Brazil
Christina Bermel Germany
Katsuaki Miki Japan
Michael Nahmou United States
Massimiliano Cristofanilli United States
Birgit Nimmervoll United States
Nikolaus Trautmann United States
Pontus Klein Germany
Philippe M. D’Onofrio Canada View profile →
Citations per field, relative to Feisi Liang
Feisi Liang · 1×
Citations per year, relative to Feisi Liang
Feisi Liang · 1×

Countries citing papers authored by Feisi Liang

Since Specialization
Citations

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

Fields of papers citing papers by Feisi Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feisi Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Feisi Liang. A scholar is included among the top collaborators of Feisi Liang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Feisi Liang. Feisi Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
# Work Indexed citations
1 45
2 52
3 71
4 93
5 111
6
RGC Neuroprotection by Manipulating ER Stress Signaling Molecules
0

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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