Yun Chai

45 total papers · 980 total citations
37 papers, 867 citations indexed

About

Yun Chai is a scholar working on Molecular Biology, Organic Chemistry and Molecular Medicine. According to data from OpenAlex, Yun Chai has authored 37 papers receiving a total of 867 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 12 papers in Organic Chemistry and 9 papers in Molecular Medicine. Recurrent topics in Yun Chai's work include Cancer therapeutics and mechanisms (14 papers), Antibiotic Resistance in Bacteria (9 papers) and Antibiotics Pharmacokinetics and Efficacy (8 papers). Yun Chai is often cited by papers focused on Cancer therapeutics and mechanisms (14 papers), Antibiotic Resistance in Bacteria (9 papers) and Antibiotics Pharmacokinetics and Efficacy (8 papers). Yun Chai collaborates with scholars based in China, United States and France. Yun Chai's co-authors include Mingliang Liu, Huiyuan Guo, Bo Wang, Lian‐Shun Feng, Kai Lv, W. David Wilson, David W. Boykin, Yibin Zhang, Ananya Paul and Xueqin Hao and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Biochemistry.

In The Last Decade

Yun Chai

37 papers receiving 856 citations

Author Peers

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

Author Last Decade Papers Cites
Yun Chai 586 447 154 120 87 37 867
Matthew B. Nodwell 362 0.6× 582 1.3× 132 0.9× 99 0.8× 64 0.7× 33 1.1k
Yushe Yang 388 0.7× 559 1.3× 109 0.7× 181 1.5× 84 1.0× 63 999
Mónica Cacho 643 1.1× 534 1.2× 124 0.8× 61 0.5× 40 0.5× 23 1.0k
Onkar Singh 509 0.9× 248 0.6× 110 0.7× 121 1.0× 56 0.6× 32 996
Yasutsugu Ueda 401 0.7× 412 0.9× 151 1.0× 224 1.9× 38 0.4× 40 877
John W. Corcoran 540 0.9× 385 0.9× 58 0.4× 185 1.5× 35 0.4× 25 970
C. Lerner 524 0.9× 440 1.0× 49 0.3× 209 1.7× 61 0.7× 22 1.0k
Mark A. Wuonola 281 0.5× 441 1.0× 140 0.9× 108 0.9× 76 0.9× 25 745
Paul Hebeisen 454 0.8× 401 0.9× 154 1.0× 158 1.3× 157 1.8× 39 966
Mark A. Seefeld 423 0.7× 563 1.3× 77 0.5× 67 0.6× 98 1.1× 20 914

Countries citing papers authored by Yun Chai

Since Specialization
Citations

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

Fields of papers citing papers by Yun Chai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yun Chai

This figure shows the co-authorship network connecting the top 25 collaborators of Yun Chai. A scholar is included among the top collaborators of Yun Chai 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 Yun Chai. Yun Chai 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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