Dié Tang

1.8k total citations · 1 hit paper
20 papers, 1.1k citations indexed

About

Dié Tang is a scholar working on Plant Science, Health, Toxicology and Mutagenesis and Atmospheric Science. According to data from OpenAlex, Dié Tang has authored 20 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Plant Science, 6 papers in Health, Toxicology and Mutagenesis and 5 papers in Atmospheric Science. Recurrent topics in Dié Tang's work include Plant Pathogens and Resistance (9 papers), Air Quality and Health Impacts (6 papers) and Chromosomal and Genetic Variations (6 papers). Dié Tang is often cited by papers focused on Plant Pathogens and Resistance (9 papers), Air Quality and Health Impacts (6 papers) and Chromosomal and Genetic Variations (6 papers). Dié Tang collaborates with scholars based in China, United States and Netherlands. Dié Tang's co-authors include Sanwen Huang, Chunzhi Zhang, Zhongmin Yang, Dawei Li, Pei Wang, Canhui Li, Yi Shang, Yu Zhan, C. Robin Buell and Zhen Peng and has published in prestigious journals such as Nature, Cell and Nature Communications.

In The Last Decade

Dié Tang

19 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Genome evolution and diversity of wild and cultivated potatoes

2022 206 citations Dié Tang, Yuxin Jia et al. Nature profile →

Peers

Dié Tang

PS

MB

FS

GENET

EE

Jiazhu Sun China

Yafang Yin China

Martti Venäläinen Finland

B. D. Singh India

Pierre Sivadon France

Rebecca A. Smith United States

Klaus Pistrick Germany

A. Susana Goggi United States

Amin K. Pathan New Zealand

Gayle H. Davidonis United States

Jiazhu Sun China

Dié Tang

1.4k ×1.8

PS

312 ×0.9

MB

38 ×0.2

FS

351 ×2.9

GENET

4 ×0.0

EE

Citations per year, relative to Dié Tang Dié Tang (= 1×) peers Jiazhu Sun

Countries citing papers authored by Dié Tang

Since Specialization

Citations

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

Fields of papers citing papers by Dié Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dié Tang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Tang, Dié, et al.. (2025). Harmonizing low-cost and regulatory air quality monitoring networks with interpretable semi-supervised learning: Reducing exposure misclassification in underrepresented communities. Journal of Hazardous Materials. 491. 137893–137893. 1 indexed citations

2.

Wang, Tong, Zhan Yu, Dié Tang, et al.. (2025). Association of Ambient Air Pollution and Temperature Exposure with Placental Abruption: A Nested Case–Control Study Based on Live Birth Registrations. Environmental Health Perspectives. 133(3-4). 47013–47013.

3.

Tang, Dié, Yu Zhan, & Fumo Yang. (2024). A review of machine learning for modeling air quality: Overlooked but important issues. Atmospheric Research. 300. 107261–107261. 44 indexed citations

4.

Tang, Dié, et al.. (2024). Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection. iScience. 27(5). 109560–109560. 2 indexed citations

5.

Tang, Dié, et al.. (2023). A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO2 pollution hotspot identification. Atmospheric Environment. 302. 119756–119756. 14 indexed citations

6.

Li, Dawei, Pei Wang, Dié Tang, et al.. (2023). Dissected Leaf 1 encodes an MYB transcription factor that controls leaf morphology in potato. Theoretical and Applied Genetics. 136(9). 183–183. 6 indexed citations

7.

Tang, Dié, Wen Zeng, Michael L. Grieneisen, et al.. (2023). Data augmentation for bias correction in mapping PM2.5 based on satellite retrievals and ground observations. Geoscience Frontiers. 15(1). 101686–101686. 10 indexed citations

8.

Tang, Dié, Yuxin Jia, Jinzhe Zhang, et al.. (2022). Genome evolution and diversity of wild and cultivated potatoes. Nature. 606(7914). 535–541. 206 indexed citations breakdown →

9.

Zhang, Jinzhe, Jian Yin, Dié Tang, et al.. (2022). Construction of homozygous diploid potato through maternal haploid induction. aBIOTECH. 3(3). 163–168. 25 indexed citations

10.

Li, Tao, Xinyi Liu, Dié Tang, et al.. (2022). Deriving Full‐Coverage and Fine‐Scale XCO₂ Across China Based on OCO‐2 Satellite Retrievals and CarbonTracker Output. Geophysical Research Letters. 49(12). 40 indexed citations

11.

Tang, Dié, Lun Zhang, Xiaoyu Zhang, et al.. (2021). Bio-Mimetic Actuators of a Photothermal-Responsive Vitrimer Liquid Crystal Elastomer with Robust, Self-Healing, Shape Memory, and Reconfigurable Properties. ACS Applied Materials & Interfaces. 14(1). 1929–1939. 56 indexed citations

12.

Tang, Dié & Qian Zhou. (2021). Research Advances in Plant Genome Assembly. 37(6). 1. 1 indexed citations

13.

Ma, Ling, Chunzhi Zhang, Fei Tang, et al.. (2021). A nonS-locus F-box gene breaks self-incompatibility in diploid potatoes. Nature Communications. 12(1). 4142–4142. 57 indexed citations

14.

Zhang, Chunzhi, Zhongmin Yang, Dié Tang, et al.. (2021). Genome design of hybrid potato. Cell. 184(15). 3873–3883.e12. 118 indexed citations

15.

Zhou, Qian, Dié Tang, Wu Huang, et al.. (2020). Haplotype-resolved genome analyses of a heterozygous diploid potato. Nature Genetics. 52(10). 1018–1023. 164 indexed citations

16.

Yang, Zhongmin, Shuangshuang Feng, Dié Tang, et al.. (2020). The mutation of a PECTATE LYASE-LIKE gene is responsible for the Yellow Margin phenotype in potato. Theoretical and Applied Genetics. 133(4). 1123–1131. 9 indexed citations

17.

Zhang, Chunzhi, Pei Wang, Dié Tang, et al.. (2019). The genetic basis of inbreeding depression in potato. Nature Genetics. 51(3). 374–378. 114 indexed citations

18.

Peng, Zhen, Pei Wang, Dié Tang, et al.. (2019). Inheritance of steroidal glycoalkaloids in potato tuber flesh. Journal of Integrative Agriculture. 18(10). 2255–2263. 13 indexed citations

19.

Tang, Dié, et al.. (2019). Comparison of GOCI and Himawari-8 aerosol optical depth for deriving full-coverage hourly PM2.5 across the Yangtze River Delta. Atmospheric Environment. 217. 116973–116973. 24 indexed citations

20.

Peng, Zhen, Dié Tang, Zhongmin Yang, et al.. (2018). Generation of self-compatible diploid potato by knockout of S-RNase. Nature Plants. 4(9). 651–654. 152 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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