Shanye Yin

88 total papers · 1.8k total citations
33 papers, 895 citations indexed

About

Shanye Yin is a scholar working on Molecular Biology, Genetics and Neurology. According to data from OpenAlex, Shanye Yin has authored 33 papers receiving a total of 895 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 9 papers in Genetics and 6 papers in Neurology. Recurrent topics in Shanye Yin's work include RNA Research and Splicing (9 papers), Chronic Lymphocytic Leukemia Research (6 papers) and RNA modifications and cancer (5 papers). Shanye Yin is often cited by papers focused on RNA Research and Splicing (9 papers), Chronic Lymphocytic Leukemia Research (6 papers) and RNA modifications and cancer (5 papers). Shanye Yin collaborates with scholars based in United States, China and Spain. Shanye Yin's co-authors include Robin Reed, Hong Ding, Wenjun Deng, Xiangyin Kong, Landian Hu, Wenjun Deng, Jaya Gangopadhyay, Haixin Lei, Steve P. Gygi and Bo Zhai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Shanye Yin

31 papers receiving 887 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shanye Yin 581 142 125 113 67 33 895
Baofeng Wang 550 0.9× 154 1.1× 224 1.8× 45 0.4× 79 1.2× 40 1.0k
Chung-Lung Cho 427 0.7× 84 0.6× 93 0.7× 94 0.8× 98 1.5× 40 975
Mrinmay Chakrabarti 602 1.0× 59 0.4× 236 1.9× 30 0.3× 57 0.9× 35 1.0k
Zhong‐Ming Qian 316 0.5× 77 0.5× 127 1.0× 123 1.1× 33 0.5× 34 841
Tz‐Chuen Ju 507 0.9× 135 1.0× 73 0.6× 42 0.4× 35 0.5× 25 837
Chuanxu Liu 464 0.8× 56 0.4× 112 0.9× 26 0.2× 82 1.2× 30 767
Nebiyu Abshiru 639 1.1× 45 0.3× 52 0.4× 137 1.2× 53 0.8× 20 836
Woo Yong Park 369 0.6× 60 0.4× 55 0.4× 29 0.3× 78 1.2× 46 773
Yukimi Kira 435 0.7× 54 0.4× 56 0.4× 38 0.3× 97 1.4× 31 941
Ava Safaroghli‐Azar 577 1.0× 45 0.3× 96 0.8× 62 0.5× 146 2.2× 45 955

Countries citing papers authored by Shanye Yin

Since Specialization
Citations

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

Fields of papers citing papers by Shanye Yin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanye Yin

This figure shows the co-authorship network connecting the top 25 collaborators of Shanye Yin. A scholar is included among the top collaborators of Shanye Yin 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 Shanye Yin. Shanye Yin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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2026