Cong Tan

3.2k total citations
32 papers, 607 citations indexed

About

Cong Tan is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Cong Tan has authored 32 papers receiving a total of 607 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Plant Science, 19 papers in Genetics and 7 papers in Molecular Biology. Recurrent topics in Cong Tan's work include Genetic Mapping and Diversity in Plants and Animals (18 papers), Wheat and Barley Genetics and Pathology (11 papers) and Plant Disease Resistance and Genetics (7 papers). Cong Tan is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (18 papers), Wheat and Barley Genetics and Pathology (11 papers) and Plant Disease Resistance and Genetics (7 papers). Cong Tan collaborates with scholars based in China, Australia and United States. Cong Tan's co-authors include Chengdao Li, Gaofeng Zhou, Yongzhong Xing, Qisen Zhang, Zhongmin Han, Xiaoqi Zhang, Sharon Westcott, Guangwei Li, Tefera Tolera Angessa and Wen Yao and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

In The Last Decade

Cong Tan

31 papers receiving 594 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cong Tan China 16 480 233 228 41 32 32 607
K. V. Prabhu India 13 613 1.3× 149 0.6× 227 1.0× 66 1.6× 13 0.4× 36 695
Sue Broughton Australia 19 842 1.8× 299 1.3× 219 1.0× 114 2.8× 23 0.7× 35 936
Ming Hao China 15 856 1.8× 276 1.2× 232 1.0× 83 2.0× 16 0.5× 73 938
Joachim Eder Germany 12 469 1.0× 256 1.1× 246 1.1× 64 1.6× 10 0.3× 25 588
Osamu Ideta Japan 14 714 1.5× 178 0.8× 375 1.6× 25 0.6× 13 0.4× 31 802
Qi Guo China 13 373 0.8× 253 1.1× 121 0.5× 38 0.9× 6 0.2× 43 506
Shigeko Utsugi Japan 11 555 1.2× 349 1.5× 73 0.3× 77 1.9× 17 0.5× 16 700
Yongjun Shu China 15 624 1.3× 332 1.4× 61 0.3× 53 1.3× 10 0.3× 55 725
L. Kuntze Germany 7 527 1.1× 152 0.7× 133 0.6× 31 0.8× 7 0.2× 11 583
Dominique Mingeot Belgium 15 595 1.2× 147 0.6× 182 0.8× 47 1.1× 5 0.2× 37 702

Countries citing papers authored by Cong Tan

Since Specialization
Citations

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

Fields of papers citing papers by Cong Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cong Tan

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

All Works

20 of 20 papers shown
1.
2.
Chen, Jiaxin, Cong Tan, Min Zhu, et al.. (2023). CropGS-Hub: a comprehensive database of genotype and phenotype resources for genomic prediction in major crops. Nucleic Acids Research. 52(D1). D1519–D1529. 15 indexed citations
3.
Shan, Ying, Yucong Zhang, Yanping Zhao, et al.. (2022). Development and validation of a cardiovascular diseases risk prediction model for Chinese males (CVDMCM). Frontiers in Cardiovascular Medicine. 9. 967097–967097. 2 indexed citations
4.
Hill, Camilla Beate, Tefera Tolera Angessa, Xiaoqi Zhang, et al.. (2021). A global barley panel revealing genomic signatures of breeding in modern Australian cultivars. The Plant Journal. 106(2). 419–434. 23 indexed citations
5.
He, Tianhua, Tefera Tolera Angessa, Camilla Beate Hill, et al.. (2021). Genomic structural equation modelling provides a whole-system approach for the future crop breeding. Theoretical and Applied Genetics. 134(9). 2875–2889. 4 indexed citations
6.
Hu, Wei, et al.. (2020). Dominant complementary interaction between OsC1 and two tightly linked genes, Rb1 and Rb2, controls the purple leaf sheath in rice. Theoretical and Applied Genetics. 133(9). 2555–2566. 18 indexed citations
7.
Wang, Yonggang, Yanhao Xu, Sanjiv Gupta, et al.. (2020). Fine mapping QSc.VR4, an effective and stable scald resistance locus in barley (Hordeum vulgare L.), to a 0.38-Mb region enriched with LRR-RLK and GLP genes. Theoretical and Applied Genetics. 133(7). 2307–2321. 3 indexed citations
8.
Li, Guangwei, Yan Zhou, Xufeng Bai, et al.. (2019). Genome-wide dissection of segregation distortion using multiple inter-subspecific crosses in rice. Science China Life Sciences. 62(4). 507–516. 12 indexed citations
9.
Hua, Wei, Cong Tan, Jingzhong Xie, et al.. (2019). Alternative splicing of a barley gene results in an excess-tillering and semi-dwarf mutant. Theoretical and Applied Genetics. 133(1). 163–177. 9 indexed citations
10.
Wang, Rong, Fei Yang, Xiaoqi Zhang, et al.. (2017). Characterization of a Thermo-Inducible Chlorophyll-Deficient Mutant in Barley. Frontiers in Plant Science. 8. 1936–1936. 13 indexed citations
11.
Han, Zhongmin, Wei Hu, Cong Tan, & Yongzhong Xing. (2017). QTLs for heading date and plant height under multiple environments in rice. Genetica. 145(1). 67–77. 19 indexed citations
12.
Jia, Qiaojun, Cong Tan, Junmei Wang, et al.. (2016). Marker development using SLAF-seq and whole-genome shotgun strategy to fine-map the semi-dwarf gene ari-e in barley. BMC Genomics. 17(1). 911–911. 24 indexed citations
13.
Li, Qiuping, Wenhao Yan, Huaxia Chen, et al.. (2016). Duplication ofOsHAPfamily genes and their association with heading date in rice. Journal of Experimental Botany. 67(6). 1759–1768. 32 indexed citations
14.
Zhang, Qisen, Xiaoqi Zhang, Songbo Wang, et al.. (2016). Involvement of Alternative Splicing in Barley Seed Germination. PLoS ONE. 11(3). e0152824–e0152824. 38 indexed citations
15.
Zhang, Li, Qiuping Li, Haijiao Dong, et al.. (2015). Three CCT domain-containing genes were identified to regulate heading date by candidate gene-based association mapping and transformation in rice. Scientific Reports. 5(1). 7663–7663. 66 indexed citations
16.
Zhou, Gaofeng, Qisen Zhang, Xiao‐Qi Zhang, Cong Tan, & Chengdao Li. (2015). Construction of High-Density Genetic Map in Barley through Restriction-Site Associated DNA Sequencing. PLoS ONE. 10(7). e0133161–e0133161. 25 indexed citations
17.
18.
Zhou, Gaofeng, Qisen Zhang, Cong Tan, Xiaoqi Zhang, & Chengdao Li. (2015). Development of genome-wide InDel markers and their integration with SSR, DArT and SNP markers in single barley map. BMC Genomics. 16(1). 804–804. 38 indexed citations
19.
Tan, Cong, Zhongmin Han, Huihui Yu, et al.. (2013). QTL Scanning for Rice Yield Using a Whole Genome SNP Array. Journal of genetics and genomics. 40(12). 629–638. 21 indexed citations
20.
Tan, Cong, Xiaoyu Weng, Wenhao Yan, Xufeng Bai, & Yongzhong Xing. (2012). <I>Ghd7</I>, a pleiotropic gene controlling flag leaf area in rice. Hereditas (Beijing). 34(7). 901–906. 8 indexed citations

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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