Y. F. Tan

1.5k total citations · 1 hit paper
7 papers, 1.2k citations indexed

About

Y. F. Tan is a scholar working on Genetics, Plant Science and Food Science. According to data from OpenAlex, Y. F. Tan has authored 7 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Genetics, 7 papers in Plant Science and 2 papers in Food Science. Recurrent topics in Y. F. Tan's work include Genetic Mapping and Diversity in Plants and Animals (5 papers), GABA and Rice Research (4 papers) and Rice Cultivation and Yield Improvement (3 papers). Y. F. Tan is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (5 papers), GABA and Rice Research (4 papers) and Rice Cultivation and Yield Improvement (3 papers). Y. F. Tan collaborates with scholars based in China, Hong Kong and United States. Y. F. Tan's co-authors include Qifa Zhang, Chao Xu, Shan Yu, M. A. Saghai Maroof, Yingxia Gao, Yongzhong Xing, Cheng Xu, Mei Sun, Harold Corke and Jinping Hua and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Theoretical and Applied Genetics and Genetic Resources and Crop Evolution.

In The Last Decade

Y. F. Tan

7 papers receiving 1.1k citations

Hit Papers

Importance of epistasis as the genetic basis of heterosis... 1997 2026 2006 2016 1997 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Y. F. Tan China 6 1.1k 980 105 48 41 7 1.2k
S. R. McCouch United States 9 1.0k 1.0× 727 0.7× 140 1.3× 18 0.4× 17 0.4× 16 1.1k
Martin Heckenberger Germany 14 848 0.8× 685 0.7× 103 1.0× 11 0.2× 26 0.6× 17 953
Merlyn S. Mendioro Philippines 20 1.2k 1.1× 352 0.4× 110 1.0× 51 1.1× 13 0.3× 36 1.2k
Wubishet A. Bekele Canada 17 677 0.6× 428 0.4× 141 1.3× 28 0.6× 38 0.9× 34 794
A. E. Corey United States 9 596 0.6× 298 0.3× 112 1.1× 27 0.6× 18 0.4× 13 627
Michel M. Beckert France 10 773 0.7× 308 0.3× 233 2.2× 35 0.7× 22 0.5× 12 836
Piotr Masojć Poland 15 809 0.8× 343 0.3× 145 1.4× 30 0.6× 10 0.2× 44 841
Masahiro Nakagahra Japan 15 570 0.5× 386 0.4× 145 1.4× 31 0.6× 22 0.5× 21 659
Timothy J. March Australia 13 628 0.6× 252 0.3× 148 1.4× 31 0.6× 32 0.8× 26 695
Osamu Ideta Japan 14 714 0.7× 375 0.4× 178 1.7× 81 1.7× 30 0.7× 31 802

Countries citing papers authored by Y. F. Tan

Since Specialization
Citations

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

Fields of papers citing papers by Y. F. Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Y. F. Tan

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

All Works

7 of 7 papers shown
1.
Qiu, Xianjin, Rong Gong, Y. F. Tan, & Sibin Yu. (2012). Mapping and characterization of the major quantitative trait locus qSS7 associated with increased length and decreased width of rice seeds. Theoretical and Applied Genetics. 125(8). 1717–1726. 55 indexed citations
2.
Costea, Mihai, David M. Brenner, François J. Tardif, Y. F. Tan, & Mei Sun. (2006). Delimitation of Amaranthus cruentus L. and Amaranthus caudatus L. using micromorphology and AFLP analysis: an application in germplasm identification. Genetic Resources and Crop Evolution. 2 indexed citations
3.
Costea, Mihai, David M. Brenner, François J. Tardif, Y. F. Tan, & Mei Sun. (2006). Delimitation of Amaranthus cruentus L. and Amaranthus caudatus L. using micromorphology and AFLP analysis: an application in germplasm identification. Genetic Resources and Crop Evolution. 53(8). 1625–1633. 31 indexed citations
4.
Yu, Shan, et al.. (2002). Identification of quantitative trait loci and epistatic interactions for plant height and heading date in rice. Theoretical and Applied Genetics. 104(4). 619–625. 110 indexed citations
5.
Tan, Y. F., Mei Sun, Yongzhong Xing, et al.. (2001). Mapping quantitative trait loci for milling quality, protein content and color characteristics of rice using a recombinant inbred line population derived from an elite rice hybrid. Theoretical and Applied Genetics. 103(6-7). 1037–1045. 133 indexed citations
6.
Tan, Y. F., et al.. (2000). Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid. Theoretical and Applied Genetics. 101(5-6). 823–829. 255 indexed citations
7.
Yu, Shan, Chao Xu, Y. F. Tan, et al.. (1997). Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid. Proceedings of the National Academy of Sciences. 94(17). 9226–9231. 586 indexed citations breakdown →

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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