Jun Tan

5.1k total citations
12 papers, 378 citations indexed

About

Jun Tan is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Jun Tan has authored 12 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Plant Science and 3 papers in Genetics. Recurrent topics in Jun Tan's work include Plant Molecular Biology Research (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers) and Non-Destructive Testing Techniques (2 papers). Jun Tan is often cited by papers focused on Plant Molecular Biology Research (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers) and Non-Destructive Testing Techniques (2 papers). Jun Tan collaborates with scholars based in China, Taiwan and India. Jun Tan's co-authors include Jun Yu, Jianguo Zhang, Lin Tao, Jun Wang, Gane Ka‐Shu Wong, Kai‐Wun Yeh, Songnian Hu, Zhonghua Zhang, Qingzhong Xue and Yajun Deng and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Genome Research and Planta.

In The Last Decade

Jun Tan

11 papers receiving 372 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Tan China 8 247 217 91 41 23 12 378
Yufeng Hua China 6 288 1.2× 314 1.4× 75 0.8× 56 1.4× 7 0.3× 7 446
Hao Gong China 9 262 1.1× 410 1.9× 106 1.2× 9 0.2× 6 0.3× 14 583
Samuel Leiboff United States 12 357 1.4× 271 1.2× 99 1.1× 31 0.8× 15 0.7× 15 435
Yoichi Kawazu Japan 11 214 0.9× 162 0.7× 106 1.2× 7 0.2× 4 0.2× 26 346
Dan Hou China 14 347 1.4× 279 1.3× 35 0.4× 59 1.4× 8 0.3× 34 466
Urs Hähnel Germany 8 416 1.7× 241 1.1× 55 0.6× 63 1.5× 5 0.2× 12 507
Pingyong Sun China 11 399 1.6× 152 0.7× 178 2.0× 6 0.1× 6 0.3× 24 487
Tohnyui Ndinyanka Fabrice Switzerland 7 555 2.2× 501 2.3× 17 0.2× 70 1.7× 6 0.3× 14 623
Yongfeng Lou China 14 426 1.7× 260 1.2× 32 0.4× 58 1.4× 11 0.5× 32 485
Pengfei Gan China 7 328 1.3× 159 0.7× 31 0.3× 4 0.1× 12 0.5× 14 372

Countries citing papers authored by Jun Tan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Tan

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

All Works

12 of 12 papers shown
1.
Tan, Jun, et al.. (2024). Glutamine maintains the stability of alveolar structure and function after lung transplantation by inhibiting autophagy. Biochemical and Biophysical Research Communications. 727. 150308–150308. 1 indexed citations
2.
Yuan, Zheng, et al.. (2021). A Passive Ferro-Particle Sensor of Lube-Oil Based on Single Permanent Magnetic Ring. IEEE Sensors Journal. 22(9). 8565–8573. 14 indexed citations
3.
Feng, Song, et al.. (2021). Sensing Model for Detecting Ferromagnetic Debris Based on a High-Gradient Magnetostatic Field. IEEE/ASME Transactions on Mechatronics. 27(5). 2440–2449. 15 indexed citations
4.
Zhang, Biao, Xiao Zhang, Hai Lan, et al.. (2021). Transcriptomic Analysis Reveals Candidate Genes Responding Maize Gray Leaf Spot Caused by Cercospora zeina. Plants. 10(11). 2257–2257. 16 indexed citations
5.
Yang, Liang, et al.. (2017). Overexpression of the maize E3 ubiquitin ligase gene ZmAIRP4 enhances drought stress tolerance in Arabidopsis. Plant Physiology and Biochemistry. 123. 34–42. 32 indexed citations
6.
Wang, Jun, et al.. (2014). Association Studies on mtDNA and Parkinson’s Disease Population Discrimination Using the Statistical Classification. Current Bioinformatics. 9(5). 481–489. 1 indexed citations
7.
Wang, Chih-Yu, et al.. (2008). Carbohydrate mobilization and gene regulatory profile in the pseudobulb of Oncidium orchid during the flowering process. Planta. 227(5). 1063–1077. 42 indexed citations
8.
Zhang, Zhonghua, Yajun Deng, Jun Tan, et al.. (2007). A Genome-wide Microsatellite Polymorphism Database for the Indica and Japonica Rice. DNA Research. 14(1). 37–45. 81 indexed citations
9.
Yang, Hua, et al.. (2005). QTL mapping of resistance to sheath blight in maize (Zea mays L.). Chinese Science Bulletin. 50(8). 782–787. 6 indexed citations
10.
Tan, Jun, et al.. (2005). Analysis of Organ-specific, Expressed Genes in Oncidium Orchid by Subtractive Expressed Sequence Tags Library. Biotechnology Letters. 27(19). 1517–1528. 26 indexed citations
11.
Liu, Qingpo, Jun Tan, & Qingzhong Xue. (2004). Effect of the flanking sequence architecture of AUG, a initiator codon on gene expression level in rice. Zhongguo nongye Kexue. 37(5). 625–629.
12.
Wong, Gane Ka‐Shu, Jun Wang, Lin Tao, et al.. (2002). Compositional Gradients in Gramineae Genes. Genome Research. 12(6). 851–856. 144 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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