Gang Yan

48 total papers · 889 total citations
36 papers, 560 citations indexed

About

Gang Yan is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Gang Yan has authored 36 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Immunology, 11 papers in Molecular Biology and 7 papers in Oncology. Recurrent topics in Gang Yan's work include Immune Cell Function and Interaction (8 papers), Computational Drug Discovery Methods (5 papers) and Diabetes and associated disorders (5 papers). Gang Yan is often cited by papers focused on Immune Cell Function and Interaction (8 papers), Computational Drug Discovery Methods (5 papers) and Diabetes and associated disorders (5 papers). Gang Yan collaborates with scholars based in United States, China and Canada. Gang Yan's co-authors include Denise L. Faustman, Lijia Shi, Denise L. Faustman, Yang Fu, Meiou Dai, Jean‐Jacques Lebrun, Suhad Ali, Cathy Lester, Sergio A. Burgos and Ni Wang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Immunology.

In The Last Decade

Gang Yan

34 papers receiving 549 citations

Author Peers

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

Author						Papers	Cites
Gang Yan	232	132	109	97	69	36	560
Ekaterina A. Lesovaya	324 1.4×	83 0.6×	123 1.1×	100 1.0×	56 0.8×	63	594
Lina Wang	228 1.0×	103 0.8×	51 0.5×	99 1.0×	22 0.3×	37	537
Harald Hundsberger	253 1.1×	93 0.7×	124 1.1×	38 0.4×	26 0.4×	35	571
Sylvie Fabrega	339 1.5×	105 0.8×	70 0.6×	79 0.8×	72 1.0×	29	587
Patricia Dranchak	341 1.5×	51 0.4×	49 0.4×	44 0.5×	45 0.7×	34	564
Yang Xu	333 1.4×	73 0.6×	50 0.5×	47 0.5×	69 1.0×	35	519
Chenyang Li	320 1.4×	99 0.8×	94 0.9×	51 0.5×	41 0.6×	47	610
Zemin Lin	292 1.3×	231 1.8×	92 0.8×	44 0.5×	16 0.2×	37	688
Hajime Sugiyama	187 0.8×	163 1.2×	57 0.5×	87 0.9×	30 0.4×	49	609
José Manuel García-Castellano	276 1.2×	61 0.5×	106 1.0×	31 0.3×	98 1.4×	26	678

Countries citing papers authored by Gang Yan

Since Specialization

Citations

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

Fields of papers citing papers by Gang Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gang Yan

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