Kun Ni

30 papers and 363 indexed citations i.

About

Kun Ni is a scholar working on Physiology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kun Ni has authored 30 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Physiology, 9 papers in Molecular Biology and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kun Ni’s work include Pain Mechanisms and Treatments (11 papers), Neuropeptides and Animal Physiology (4 papers) and Neuroinflammation and Neurodegeneration Mechanisms (4 papers). Kun Ni is often cited by papers focused on Pain Mechanisms and Treatments (11 papers), Neuropeptides and Animal Physiology (4 papers) and Neuroinflammation and Neurodegeneration Mechanisms (4 papers). Kun Ni collaborates with scholars based in China, Germany and Ukraine. Kun Ni's co-authors include Dorit Möhrle, Marlies Knipper, Lukas Rüttiger, Dan Bing, Sze Chim Lee, Ulrike Zimmermann, Limin Zhao, Yue Sun, Zhengliang Ma and Jiali Wu and has published in prestigious journals such as Angewandte Chemie International Edition, Neuroscience and Science Translational Medicine.

In The Last Decade

Co-authorship network of co-authors of Kun Ni i

Fields of papers citing papers by Kun Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Kun Ni

Since Specialization
Citations

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

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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2025