Jing Tan

1.4k total citations
35 papers, 1.1k citations indexed

About

Jing Tan is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Jing Tan has authored 35 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Plant Science, 14 papers in Genetics and 8 papers in Molecular Biology. Recurrent topics in Jing Tan's work include Genetics and Plant Breeding (11 papers), Genetic Mapping and Diversity in Plants and Animals (10 papers) and Genetic and phenotypic traits in livestock (4 papers). Jing Tan is often cited by papers focused on Genetics and Plant Breeding (11 papers), Genetic Mapping and Diversity in Plants and Animals (10 papers) and Genetic and phenotypic traits in livestock (4 papers). Jing Tan collaborates with scholars based in China, United States and Philippines. Jing Tan's co-authors include Manjit S. Kang, Xingming Fan, Xingming Fan, Yudong Zhang, Hongmei Chen, Karabi Datta, Mayank Rai, Swapan K. Datta, Norman Oliva and Lina Torrizo and has published in prestigious journals such as Nucleic Acids Research, The Science of The Total Environment and Molecular Ecology.

In The Last Decade

Jing Tan

35 papers receiving 977 citations

Peers

Jing Tan

GENET

EEBS

Wesley Bruce United States

Nick Lauter United States

Joanne A. Labate United States

Ana Clara Pontaroli Argentina

B. Skovmand Mexico

Ivan Schuster Brazil

S. K. Raina India

Gennaro Fazio United States

Phillip A. Wadl United States

Imad A. Eujayl United States

Wesley Bruce United States

Jing Tan

837 ×1.1

184 ×0.4

GENET

428 ×1.8

167 ×0.9

96 ×0.6

EEBS

Citations per year, relative to Jing Tan Jing Tan (= 1×) peers Wesley Bruce

Countries citing papers authored by Jing Tan

Since Specialization

Citations

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

Fields of papers citing papers by Jing Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Tan

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

All Works

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20 of 20 papers shown

Zhu, Ling, Zhiqiang Xie, Lihong Yang, et al.. (2025). Spatiotemporal evolution and driving factors of urban form resilience under flood hazard disturbance: A case study of 137 cities in the southeast monsoon influence zone of China. The Science of The Total Environment. 990. 179889–179889. 2 indexed citations

Xu, Yunjian, Zhe Chen, Xiaoyu Li, et al.. (2023). The mechanism of promoting rhizosphere nutrient turnover for arbuscular mycorrhizal fungi attributes to recruited functional bacterial assembly. Molecular Ecology. 32(9). 2335–2350. 25 indexed citations

Xu, Yunjian, Zhe Chen, Xiaoyu Li, et al.. (2022). Mycorrhizal fungi alter root exudation to cultivate a beneficial microbiome for plant growth. Functional Ecology. 37(3). 664–675. 41 indexed citations

Tan, Jing, Junjie Guo, Mingyu Yin, et al.. (2018). Next Generation Sequencing-Based Molecular Marker Development: A Case Study in Betula Alnoides. Molecules. 23(11). 2963–2963. 5 indexed citations

Tan, Jing, Zhigang Zhao, Junjie Guo, Chunsheng Wang, & Jie Zeng. (2018). Genetic Diversity and Population Genetic Structure of Erythrophleum fordii Oliv., an Endangered Rosewood Species in South China. Forests. 9(10). 636–636. 6 indexed citations

Xu, Ling, Yan Zhang, Wei Chen, et al.. (2014). High-resolution mapping and characterization of qRgls2, a major quantitative trait locus involved in maize resistance to gray leaf spot. BMC Plant Biology. 14(1). 230–230. 29 indexed citations

Zhang, Yan, Ling Xu, Xingming Fan, et al.. (2012). QTL mapping of resistance to gray leaf spot in maize. Theoretical and Applied Genetics. 125(8). 1797–1808. 44 indexed citations

Kang, Manjit S., et al.. (2010). IMPROVING GRAIN YIELD AND YIELD COMPONENTS VIA BACKCROSS PROCEDURE. Maydica. 55(2). 145–153. 7 indexed citations

Tan, Jing, et al.. (2010). Screening of Maize Hybrids and Identifying of Selecting Indicator for Drought Tolerance. Yunnan Nongye Daxue xuebao. 25(2). 189–194. 1 indexed citations

10.

Luo, Liming, et al.. (2009). Heterotic grouping of 27 maize inbred lined divided by simple sequence repeats (SSR) markers and yields.. Yumi kexue. 17(1). 54–58. 1 indexed citations

11.

Fan, Xingming, et al.. (2008). A New Maize Heterotic Pattern between Temperate and Tropical Germplasms. Agronomy Journal. 100(4). 917–923. 45 indexed citations

12.

Rai, Mayank, Karabi Datta, Vilas Parkhi, et al.. (2007). Variable T-DNA linkage configuration affects inheritance of carotenogenic transgenes and carotenoid accumulation in transgenic indica rice. Plant Cell Reports. 26(8). 1221–1231. 29 indexed citations

13.

Datta, Karabi, Mayank Rai, Vilas Parkhi, et al.. (2006). Improved 'golden' indica rice and post-transgeneration enhancement of metabolic target products of carotenoids (b-carotene) in transgenic elite cultivars (IR64 and BR29). Current Science. 91(7). 935–939. 20 indexed citations

14.

Tan, Jing, et al.. (2006). Analysis of yield combining ability of subtropical tropical quality protein maize inbred line and temperate normal maize inbred line. Yumi kexue. 14(1). 12–1545. 3 indexed citations

15.

Baisakh, Niranjan, Mayank Rai, Norman Oliva, et al.. (2006). Marker‐free transgenic (MFT) near‐isogenic introgression lines (NIILs) of ‘golden’ indica rice (cv. IR64) with accumulation of provitamin A in the endosperm tissue. Plant Biotechnology Journal. 4(4). 467–475. 18 indexed citations

16.

Parkhi, Vilas, Mayank Rai, Jing Tan, et al.. (2005). Molecular characterization of marker-free transgenic lines of indica rice that accumulate carotenoids in seed endosperm. Molecular Genetics and Genomics. 274(4). 325–336. 37 indexed citations

17.

Fan, Xingming, et al.. (2004). Combining ability and heterotic grouping of ten temperate, subtropical and tropical quality protein maize inbreds [Zea mays L.]. Maydica. 49(4). 267–272. 16 indexed citations

18.

Datta, Karabi, Niranjan Baisakh, Norman Oliva, et al.. (2003). Bioengineered ‘ golden ’ indica rice cultivars with β‐carotene metabolism in the endosperm with hygromycin and mannose selection systems. Plant Biotechnology Journal. 1(2). 81–90. 109 indexed citations

19.

Tan, Jing, et al.. (2001). Analyses of Combining Ability and Heterotic Group of Yellow Grain Quality Protein Maize Inbreeds. 23(6). 547–552. 12 indexed citations

20.

Moore, Bethany B., et al.. (1993). Regulatory elements necessary for termination of transcription within the Ig heavy chain gene locus. Nucleic Acids Research. 21(6). 1481–1488. 7 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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