Qiong Gu

6.6k total citations · 2 hit papers
193 papers, 4.9k citations indexed

About

Qiong Gu is a scholar working on Molecular Biology, Pharmacology and Oncology. According to data from OpenAlex, Qiong Gu has authored 193 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 124 papers in Molecular Biology, 39 papers in Pharmacology and 36 papers in Oncology. Recurrent topics in Qiong Gu's work include Computational Drug Discovery Methods (35 papers), Drug Transport and Resistance Mechanisms (18 papers) and Bone Metabolism and Diseases (15 papers). Qiong Gu is often cited by papers focused on Computational Drug Discovery Methods (35 papers), Drug Transport and Resistance Mechanisms (18 papers) and Bone Metabolism and Diseases (15 papers). Qiong Gu collaborates with scholars based in China, United States and Norway. Qiong Gu's co-authors include Jun Xu, Douglas E. Kargman, Ralph L. Sacco, Huihao Zhou, Yuying Fang, Qingyun Tan, Xiu‐Cai Chen, Xin Yan, Zhihong Liu and Ji‐Jun Chen and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Qiong Gu

188 papers receiving 4.8k citations

Hit Papers

Race-Ethnicity and Determinants of Intracranial Atheroscl... 1995 2026 2005 2015 1995 2021 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qiong Gu China 37 2.2k 1.1k 881 652 642 193 4.9k
Wei Xiao China 44 3.6k 1.6× 265 0.2× 477 0.5× 487 0.7× 944 1.5× 433 7.9k
Guang Liang China 57 5.6k 2.5× 777 0.7× 949 1.1× 228 0.3× 830 1.3× 386 11.3k
Liang Liu Macao 47 3.6k 1.6× 290 0.3× 570 0.6× 207 0.3× 1.1k 1.7× 210 7.0k
Vincent Kam Wai Wong Macao 39 2.5k 1.1× 207 0.2× 781 0.9× 214 0.3× 410 0.6× 183 4.5k
Yong Wang China 42 5.1k 2.3× 329 0.3× 713 0.8× 262 0.4× 1.4k 2.3× 259 8.2k
Ying Xie China 47 3.4k 1.5× 598 0.5× 472 0.5× 145 0.2× 666 1.0× 288 7.7k
Jiarui Wu China 30 1.8k 0.8× 593 0.5× 479 0.5× 286 0.4× 335 0.5× 247 4.3k
Guang Liang China 40 2.3k 1.0× 351 0.3× 621 0.7× 128 0.2× 420 0.7× 129 4.7k
Yonghua Wang China 40 4.8k 2.2× 357 0.3× 446 0.5× 2.5k 3.9× 1.5k 2.3× 139 9.3k
Ajit Jadhav United States 50 5.1k 2.3× 226 0.2× 636 0.7× 1.3k 2.0× 541 0.8× 150 8.1k

Countries citing papers authored by Qiong Gu

Since Specialization
Citations

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

Fields of papers citing papers by Qiong Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiong Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Qiong Gu. A scholar is included among the top collaborators of Qiong Gu 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 Qiong Gu. Qiong Gu 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.
Xu, Peng, et al.. (2025). Development of potent inhibitors targeting bacterial prolyl-tRNA synthetase through fluorine scanning-directed activity tuning. European Journal of Medicinal Chemistry. 291. 117647–117647.
2.
Gu, Qiong, et al.. (2025). Chemical constituents and their anti-ferroptosis activities of Ajuga bracteosa. Fitoterapia. 182. 106444–106444. 1 indexed citations
3.
Xu, Jun, et al.. (2024). Biochemical and structural characterization of chlorhexidine as an ATP-assisted inhibitor against type 1 methionyl-tRNA synthetase from Gram-positive bacteria. European Journal of Medicinal Chemistry. 268. 116303–116303. 3 indexed citations
4.
Peng, Xing, et al.. (2024). Chemical Constituents of Ajuga Lupulina and their Anti‐Ferroptosis Activity. Chemistry & Biodiversity. 21(4). e202400244–e202400244. 1 indexed citations
5.
Han, Lu, Taotao Zou, Junjian Wang, et al.. (2023). The binding mode of orphan glycyl-tRNA synthetase with tRNA supports the synthetase classification and reveals large domain movements. Science Advances. 9(6). eadf1027–eadf1027. 12 indexed citations
6.
Peng, Xing, et al.. (2023). Chemical constituents of Ajuga forrestii and their anti-ferroptosis activity. Fitoterapia. 166. 105461–105461. 4 indexed citations
7.
Fang, Yuying, Qingyun Tan, Huihao Zhou, Qiong Gu, & Jun Xu. (2022). Discovery of novel diphenylbutene derivative ferroptosis inhibitors as neuroprotective agents. European Journal of Medicinal Chemistry. 231. 114151–114151. 27 indexed citations
9.
Gu, Qiong, et al.. (2021). Inhibitory mechanism of reveromycin A at the tRNA binding site of a class I synthetase. Nature Communications. 12(1). 1616–1616. 21 indexed citations
10.
Gu, Qiong, et al.. (2021). Author Correction: Inhibitory mechanism of reveromycin A at the tRNA binding site of a class I synthetase. Nature Communications. 12(1). 2533–2533. 1 indexed citations
11.
Liu, Zhihong, Dane Huang, Shuangjia Zheng, et al.. (2020). Deep learning enables discovery of highly potent anti-osteoporosis natural products. European Journal of Medicinal Chemistry. 210. 112982–112982. 29 indexed citations
12.
Li, Liya, Hang Ma, Tingting Liu, et al.. (2020). Glucitol-core containing gallotannins-enriched red maple (Acer rubrum) leaves extract alleviated obesity via modulating short-chain fatty acid production in high-fat diet-fed mice. Journal of Functional Foods. 70. 103970–103970. 18 indexed citations
13.
Du, Jialiang, et al.. (2020). The endemic GII.4 norovirus‐like‐particle induced‐antibody lacks of cross‐reactivity against the epidemic GII.17 strain. Journal of Medical Virology. 93(6). 3974–3979. 4 indexed citations
14.
Pei, Hua, Chao Zhao, Huihao Zhou, et al.. (2020). Jatrophane Diterpenoids from Euphorbia esula as Inhibitors of RANKL-Induced Osteoclastogenesis. Journal of Natural Products. 83(4). 1005–1017. 16 indexed citations
15.
Wang, Qian, Nannan Zhu, Yan Wang, et al.. (2020). The mTOR inhibitor manassantin B reveals a crucial role of mTORC2 signaling in Epstein-Barr virus reactivation. Journal of Biological Chemistry. 295(21). 7431–7441. 19 indexed citations
16.
Zhou, Xiaowei, Ying Li, Mingyu Zhang, et al.. (2019). Spectrum-Effect Relationship between UPLC Fingerprints and Antilung Cancer Effect of Si Jun Zi Tang. Evidence-based Complementary and Alternative Medicine. 2019. 1–9. 16 indexed citations
17.
Zhou, Lin, Qian Liu, Guoju Hong, et al.. (2019). Cumambrin A prevents OVX‐induced osteoporosis via the inhibition of osteoclastogenesis, bone resorption, and RANKL signaling pathways. The FASEB Journal. 33(6). 6726–6735. 14 indexed citations
18.
Cui, Hui, Yena Liu, Qiong Gu, et al.. (2018). Ethylnaphthoquinone derivatives as inhibitors of indoleamine-2, 3-dioxygenase from the mangrove endophytic fungus Neofusicoccum austral SYSU-SKS024. Fitoterapia. 125. 281–285. 15 indexed citations
19.
Chen, Ziwei, Maria Digiacomo, Yalin Tu, et al.. (2016). Discovery of novel rivastigmine-hydroxycinnamic acid hybrids as multi-targeted agents for Alzheimer's disease. European Journal of Medicinal Chemistry. 125. 784–792. 59 indexed citations
20.
Li, Yali, Ling Wang, Zhihong Liu, et al.. (2015). Predicting selective liver X receptor β agonists using multiple machine learning methods. Molecular BioSystems. 11(5). 1241–1250. 21 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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