Jin Tan

43 papers and 2.6k indexed citations i.

About

Jin Tan is a scholar working on Molecular Biology, Epidemiology and Cancer Research. According to data from OpenAlex, Jin Tan has authored 43 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 18 papers in Epidemiology and 14 papers in Cancer Research. Recurrent topics in Jin Tan’s work include Autophagy in Disease and Therapy (18 papers), Extracellular vesicles in disease (12 papers) and MicroRNA in disease regulation (9 papers). Jin Tan is often cited by papers focused on Autophagy in Disease and Therapy (18 papers), Extracellular vesicles in disease (12 papers) and MicroRNA in disease regulation (9 papers). Jin Tan collaborates with scholars based in China and United States. Jin Tan's co-authors include Yuyang Miao, Qiang Zhang, Shuling Song, Lulu Li, Ping Lei, Mengmeng Li, Zhaoli Han, Fanglian Chen, Xintong Ge and Ping Lei and has published in prestigious journals such as Brain Research, Journal of Cellular Physiology and Cell Death and Disease.

In The Last Decade

Co-authorship network of co-authors of Jin Tan i

Fields of papers citing papers by Jin Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Jin Tan

Since Specialization
Citations

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