Dagang Chen

3.3k total citations · 1 hit paper
48 papers, 2.7k citations indexed

About

Dagang Chen is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Dagang Chen has authored 48 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 13 papers in Plant Science and 11 papers in Genetics. Recurrent topics in Dagang Chen's work include Cancer-related gene regulation (7 papers), Rice Cultivation and Yield Improvement (7 papers) and Genetic Mapping and Diversity in Plants and Animals (6 papers). Dagang Chen is often cited by papers focused on Cancer-related gene regulation (7 papers), Rice Cultivation and Yield Improvement (7 papers) and Genetic Mapping and Diversity in Plants and Animals (6 papers). Dagang Chen collaborates with scholars based in China, United States and Australia. Dagang Chen's co-authors include Michael R. Stallcup, Stephen S. Koh, Shih‐Ming Huang, Brandon T. Schurter, Dana W. Aswad, Han Ma, Heng Hong, Young‐Ho Lee, Catherine Teyssier and Joel M. Harp and has published in prestigious journals such as Science, Journal of Biological Chemistry and Biochemistry.

In The Last Decade

Dagang Chen

45 papers receiving 2.7k citations

Hit Papers

Regulation of Transcription by a Protein Methyltransferase 1999 2026 2008 2017 1999 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dagang Chen China 15 2.1k 865 272 148 143 48 2.7k
Michael R. Hübner United States 9 2.2k 1.0× 1.0k 1.2× 370 1.4× 127 0.9× 82 0.6× 9 2.6k
Elisabeth Scheer France 20 2.0k 0.9× 1.1k 1.3× 299 1.1× 180 1.2× 50 0.3× 30 2.5k
Daniel Robyr Switzerland 17 1.5k 0.7× 434 0.5× 247 0.9× 95 0.6× 67 0.5× 22 1.9k
Bertrand Le Douarin France 12 1.7k 0.8× 827 1.0× 202 0.7× 110 0.7× 78 0.5× 13 2.0k
Juan Inostroza United States 10 1.8k 0.9× 1.2k 1.4× 315 1.2× 239 1.6× 107 0.7× 10 2.3k
Ernest Martinez United States 29 3.0k 1.4× 1.0k 1.2× 384 1.4× 205 1.4× 97 0.7× 49 3.8k
Han Ma United States 12 2.2k 1.0× 855 1.0× 240 0.9× 266 1.8× 210 1.5× 12 2.6k
Christopher Leo United States 10 945 0.4× 576 0.7× 242 0.9× 103 0.7× 51 0.4× 11 1.3k
Martin Koš Germany 21 2.5k 1.2× 1.2k 1.4× 460 1.7× 230 1.6× 81 0.6× 32 3.1k
Dennis H. Dowhan Australia 23 1.6k 0.8× 438 0.5× 445 1.6× 122 0.8× 55 0.4× 28 2.2k

Countries citing papers authored by Dagang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Dagang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dagang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Dagang Chen. A scholar is included among the top collaborators of Dagang Chen 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 Dagang Chen. Dagang Chen 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.
Ye, Chanjuan, Feng‐Ling Si, Jie Guo, et al.. (2025). GW2-mediated ubiquitination and degradation of YLR regulate grain size and leaf color by coordinating source-sink modulation. PLANT PHYSIOLOGY. 200(2).
2.
Chen, Ke, Jie Guo, Chanjuan Ye, et al.. (2025). Advances in resistant starch: mechanisms, applications, and challenges in obesity management and low-fat food development. International Journal of Biological Macromolecules. 320(Pt 1). 145679–145679. 1 indexed citations
3.
Wang, Jian, Dagang Chen, Haifei Hu, et al.. (2025). Functional characterization of OsLT9 in regulating rice leaf thickness. Journal of genetics and genomics. 53(2). 223–233. 1 indexed citations
4.
Guo, Jie, et al.. (2024). Effect of Fat Content on Rice Taste Quality through Transcriptome Analysis. Genes. 15(1). 81–81. 8 indexed citations
5.
Chen, Dagang, et al.. (2024). A Simple Narrative Review of Progress on the Processing and Utilization of Functional Rice. Foods. 13(23). 3911–3911.
6.
Ye, Chanjuan, Jie Guo, Dagang Chen, et al.. (2023). The Dsup coordinates grain development and abiotic stress in rice. Plant Physiology and Biochemistry. 205. 108184–108184. 8 indexed citations
8.
Chen, Dagang, et al.. (2023). 1H NMR-Based Metabolic Profiling to Follow Changes in Pomelo Cultivars during Postharvest Senescence. Foods. 12(10). 2001–2001. 1 indexed citations
9.
Guo, Jie, Ke Chen, Chanjuan Ye, et al.. (2023). Genetic Analysis of S5 Regulating the Hybrid Sterility between Indica and Japonica Subspecies in Rice. Agronomy. 13(4). 1094–1094. 1 indexed citations
10.
Chen, Dagang, et al.. (2023). Pyramiding Breeding of Low-Glutelin-Content Indica Rice with Good Quality and Resistance. Plants. 12(21). 3763–3763. 4 indexed citations
11.
Zhuang, Xiaoyu, et al.. (2022). FAM84B promotes the proliferation of glioma cells through the cell cycle pathways. World Journal of Surgical Oncology. 20(1). 368–368. 10 indexed citations
12.
Chen, Dagang, et al.. (2022). Fine-mapping and candidate gene analysis of a major locus controlling leaf thickness in rice (Oryza sativa L.). Molecular Breeding. 42(2). 6–6. 8 indexed citations
13.
14.
Hu, Jack, et al.. (2010). Computational investigation of the Anti-HIV activity of Chinese medicinal formula Three-Huang Powder. Interdisciplinary Sciences Computational Life Sciences. 2(2). 151–156. 15 indexed citations
15.
Chen, Shen Liang, Kelly A. Loffler, Dagang Chen, Michael R. Stallcup, & George E.O. Muscat. (2002). The Coactivator-associated Arginine Methyltransferase Is Necessary for Muscle Differentiation. Journal of Biological Chemistry. 277(6). 4324–4333. 134 indexed citations
16.
Teyssier, Catherine, Dagang Chen, & Michael R. Stallcup. (2002). Requirement for Multiple Domains of the Protein Arginine Methyltransferase CARM1 in Its Transcriptional Coactivator Function. Journal of Biological Chemistry. 277(48). 46066–46072. 85 indexed citations
17.
Koh, Stephen S., Dagang Chen, Young‐Ho Lee, & Michael R. Stallcup. (2001). Synergistic Enhancement of Nuclear Receptor Function by p160 Coactivators and Two Coactivators with Protein Methyltransferase Activities. Journal of Biological Chemistry. 276(2). 1089–1098. 292 indexed citations
18.
Chen, Dagang, Shih‐Ming Huang, & Michael R. Stallcup. (2000). Synergistic, p160 Coactivator-dependent Enhancement of Estrogen Receptor Function by CARM1 and p300. Journal of Biological Chemistry. 275(52). 40810–40816. 201 indexed citations
19.
DiLorenzo, Teresa P., Dagang Chen, Ping Zhang, & Bettie M. Steinberg. (1998). Evidence for the Separate Regulation of the Human Papillomavirus Type 11 E7 and E6 Promoters by ViralcisSequences near the E6 Promoter. Virology. 243(1). 130–139. 3 indexed citations
20.
Webb, Paul, Phuong Nguyen, J. Shinsako, et al.. (1998). Estrogen Receptor Activation Function 1 Works by Binding p160 Coactivator Proteins. Molecular Endocrinology. 12(10). 1605–1618. 313 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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