Han Dai

3.3k total citations · 2 hit papers
41 papers, 2.4k citations indexed

About

Han Dai is a scholar working on Molecular Biology, Cell Biology and Geriatrics and Gerontology. According to data from OpenAlex, Han Dai has authored 41 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 11 papers in Cell Biology and 6 papers in Geriatrics and Gerontology. Recurrent topics in Han Dai's work include Cellular transport and secretion (9 papers), Lipid Membrane Structure and Behavior (8 papers) and Sirtuins and Resveratrol in Medicine (6 papers). Han Dai is often cited by papers focused on Cellular transport and secretion (9 papers), Lipid Membrane Structure and Behavior (8 papers) and Sirtuins and Resveratrol in Medicine (6 papers). Han Dai collaborates with scholars based in China, United States and United Kingdom. Han Dai's co-authors include Josep Rizo, Thomas C. Südhof, James L. Ellis, David Sinclair, Clemens Steegborn, Ok-Ho Shin, Jiong Tang, Anton Maximov, Robert B. Perni and Irina Dulubova and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Han Dai

39 papers receiving 2.4k citations

Hit Papers

Sirtuin activators and inhibitors... 2006 2026 2012 2019 2018 2006 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Han Dai China 20 1.5k 793 656 373 352 41 2.4k
Yan Shang China 34 1.8k 1.2× 134 0.2× 514 0.8× 491 1.3× 392 1.1× 85 3.1k
Rong Shao United States 15 2.3k 1.6× 346 0.4× 101 0.2× 153 0.4× 291 0.8× 29 3.2k
Chuangui Wang China 27 1.7k 1.1× 249 0.3× 499 0.8× 189 0.5× 347 1.0× 42 2.4k
Christian Dölle Norway 20 1.4k 1.0× 91 0.1× 803 1.2× 328 0.9× 373 1.1× 35 2.8k
Narimichi Kimura Japan 30 2.3k 1.5× 159 0.2× 159 0.2× 185 0.5× 187 0.5× 81 2.9k
Tanjun Tong China 33 2.2k 1.5× 138 0.2× 343 0.5× 897 2.4× 290 0.8× 100 3.4k
Yingjie Shen China 20 1.2k 0.8× 574 0.7× 82 0.1× 138 0.4× 150 0.4× 46 2.4k
Ivana Celardo United Kingdom 15 1.2k 0.8× 172 0.2× 73 0.1× 306 0.8× 236 0.7× 21 2.9k
Laura Emionite Italy 29 1.2k 0.8× 66 0.1× 85 0.1× 476 1.3× 173 0.5× 74 2.6k
Luisa Quinti United States 15 548 0.4× 44 0.1× 328 0.5× 295 0.8× 192 0.5× 25 1.3k

Countries citing papers authored by Han Dai

Since Specialization
Citations

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

Fields of papers citing papers by Han Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Han Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Han Dai. A scholar is included among the top collaborators of Han Dai 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 Han Dai. Han Dai 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.
Chen, Bo, Wenfeng Huang, Wenbo Guo, et al.. (2025). Iron- and Manganese-Catalyzed Maillard Chemistry: Molecular Characteristics, Evolution Pathways, and Implications for Soil Organic Carbon Formation. Environmental Science & Technology. 59(42). 22587–22598.
3.
Tang, Huan, et al.. (2024). The application of nanodiscs in membrane protein drug discovery & development and drug delivery. Frontiers in Chemistry. 12. 3 indexed citations
4.
Liu, Yanlei, Minglin Wang, Xinyue Liang, et al.. (2024). Transcriptional signatures of secondary hair follicles during annual cashmere growth. Scientific Data. 11(1). 1427–1427. 1 indexed citations
5.
Dai, Han, Shanshan He, Jie Han, & Baoshan Xing. (2024). Mask Wearers at Risk of Inhaling Respirable Hazards from Leave-On Facial Cosmetics. Environmental Science & Technology. 58(49). 21464–21474. 1 indexed citations
6.
Wang, Minglin, Han Dai, Yanlei Liu, et al.. (2023). Discovery and Functional Analysis of Secondary Hair Follicle miRNAs during Annual Cashmere Growth. International Journal of Molecular Sciences. 24(2). 1063–1063. 12 indexed citations
7.
Law, Robert P., João Nunes, Chun‐wa Chung, et al.. (2021). Discovery and Characterisation of Highly Cooperative FAK‐Degrading PROTACs. Angewandte Chemie International Edition. 60(43). 23327–23334. 85 indexed citations
8.
Law, Robert P., João Nunes, Chun‐wa Chung, et al.. (2021). Discovery and Characterisation of Highly Cooperative FAK‐Degrading PROTACs. Angewandte Chemie. 133(43). 23515–23522. 4 indexed citations
9.
Chung, Chun‐wa, Han Dai, Esther Fernández, et al.. (2020). Structural Insights into PROTAC-Mediated Degradation of Bcl-xL. ACS Chemical Biology. 15(9). 2316–2323. 67 indexed citations
10.
Anderson, Niall A., et al.. (2020). Selective CDK6 degradation mediated by cereblon, VHL, and novel IAP-recruiting PROTACs. Bioorganic & Medicinal Chemistry Letters. 30(9). 127106–127106. 50 indexed citations
11.
Tang, Dongfang, Yuqin Yang, Zhen Xiao, et al.. (2020). Scorpion toxin inhibits the voltage‐gated proton channel using a Zn2+‐like long‐range conformational coupling mechanism. British Journal of Pharmacology. 177(10). 2351–2364. 16 indexed citations
12.
Tinworth, Christopher P., Zuni I. Bassi, Marcel Muelbaier, et al.. (2019). PROTAC-Mediated Degradation of Bruton’s Tyrosine Kinase Is Inhibited by Covalent Binding. ACS Chemical Biology. 14(3). 342–347. 134 indexed citations
13.
Huang, Bin, Chaochao Lai, Han Dai, et al.. (2019). Microbially reduced humic acid promotes the anaerobic photodegradation of 17α-ethinylestradiol. Ecotoxicology and Environmental Safety. 171. 313–320. 14 indexed citations
14.
Dai, Han, David Sinclair, James L. Ellis, & Clemens Steegborn. (2018). Sirtuin activators and inhibitors: Promises, achievements, and challenges. Pharmacology & Therapeutics. 188. 140–154. 359 indexed citations breakdown →
15.
Dai, Han, James L. Ellis, David Sinclair, & Basil P. Hubbard. (2016). Synthesis and Assay of SIRT1-Activating Compounds. Methods in enzymology on CD-ROM/Methods in enzymology. 574. 213–244. 7 indexed citations
16.
Dai, Han, David P. Carney, April Case, et al.. (2010). SIRT1 Activation by Small Molecules. Journal of Biological Chemistry. 285(43). 32695–32703. 175 indexed citations
17.
Dai, Han, Nan Shen, Demet Araç, & Josep Rizo. (2007). A Quaternary SNARE–Synaptotagmin–Ca2+–Phospholipid Complex in Neurotransmitter Release. Journal of Molecular Biology. 367(3). 848–863. 92 indexed citations
18.
Roggero, Carlos M., Gerardo A. De Blas, Han Dai, et al.. (2007). Complexin/Synaptotagmin Interplay Controls Acrosomal Exocytosis. Journal of Biological Chemistry. 282(36). 26335–26343. 59 indexed citations
19.
Lu, Jun, Mischa Machius, Irina Dulubova, et al.. (2006). Structural Basis for a Munc13–1 Homodimer to Munc13–1/RIM Heterodimer Switch. PLoS Biology. 4(7). e192–e192. 95 indexed citations
20.
Zhong, Jun, Zhi‐mei Qi, Han Dai, et al.. (2003). Sensing Phenothiazine Drugs at a Gold Electrode Co-modified with DNA and Gold Nanoparticles. Analytical Sciences. 19(5). 653–657. 36 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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