Lingzhi Qu

1.5k total citations
46 papers, 1.2k citations indexed

About

Lingzhi Qu is a scholar working on Molecular Biology, Oncology and Materials Chemistry. According to data from OpenAlex, Lingzhi Qu has authored 46 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 8 papers in Oncology and 8 papers in Materials Chemistry. Recurrent topics in Lingzhi Qu's work include Quantum Dots Synthesis And Properties (8 papers), Fibroblast Growth Factor Research (7 papers) and Nanocluster Synthesis and Applications (7 papers). Lingzhi Qu is often cited by papers focused on Quantum Dots Synthesis And Properties (8 papers), Fibroblast Growth Factor Research (7 papers) and Nanocluster Synthesis and Applications (7 papers). Lingzhi Qu collaborates with scholars based in China, United States and India. Lingzhi Qu's co-authors include Dawei Deng, Yueqing Gu, Yongheng Chen, Zhuchu Chen, Longying Jiang, Samuel Achilefu, Shuyan Dai, Hudie Wei, Xiaojuan Chen and Xujun Liang and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Lingzhi Qu

45 papers receiving 1.2k citations

Peers

Lingzhi Qu

EEE

CTM

ONCOL

Takayo Inoue United States

Andreas Krämer Germany

Liangcai Zhang China

Weina Ma China

Lianlian Wu China

Hui‐Ling Cao China

Yuxuan Hu China

Tianyun Liu United States

Yuanzhong Chen China

Brent M. Kuenzi United States

Takayo Inoue United States

Lingzhi Qu

758 ×1.2

190 ×0.5

209 ×1.0

EEE

66 ×0.5

CTM

186 ×1.4

ONCOL

Citations per year, relative to Lingzhi Qu Lingzhi Qu (= 1×) peers Takayo Inoue

Countries citing papers authored by Lingzhi Qu

Since Specialization

Citations

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

Fields of papers citing papers by Lingzhi Qu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingzhi Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Lingzhi Qu. A scholar is included among the top collaborators of Lingzhi Qu 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 Lingzhi Qu. Lingzhi Qu 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

Lin, Hang, Lingzhi Qu, Hudie Wei, et al.. (2025). Characterization of Bozitinib as a potential therapeutic agent for MET-amplified gastric cancer. Communications Biology. 8(1). 134–134.

Wei, Hudie, Haolan Wang, Jiaqi Wang, et al.. (2025). Deciphering molecular specificity in MCL-1/BAK interaction and its implications for designing potent MCL-1 inhibitors. Cell Death and Differentiation. 32(6). 991–999. 4 indexed citations

Dai, Shuyan, et al.. (2024). Structural basis and selectivity of sulfatinib binding to FGFR and CSF-1R. Communications Chemistry. 7(1). 3–3. 6 indexed citations

Li, Hui‐Liang, Shuyan Dai, Lingzhi Qu, et al.. (2024). Design, synthesis, and biological evaluation of selective covalent inhibitors of FGFR4. European Journal of Medicinal Chemistry. 268. 116281–116281. 4 indexed citations

Wei, Hudie, Haolan Wang, Lingzhi Qu, et al.. (2023). Structures of p53/BCL-2 complex suggest a mechanism for p53 to antagonize BCL-2 activity. Nature Communications. 14(1). 4300–4300. 58 indexed citations

Liang, Xujun, Ying Fu, Lingzhi Qu, Pengfei Zhang, & Yongheng Chen. (2023). Prediction of drug side effects with transductive matrix co-completion. Bioinformatics. 39(1). 6 indexed citations

Lin, Hang, et al.. (2023). Comprehensive analysis of necroptosis-related lncRNA signature with potential implications in tumor heterogeneity and prediction of prognosis in clear cell renal cell carcinoma. European journal of medical research. 28(1). 236–236. 4 indexed citations

Liang, Xujun, Jun Li, Ying Fu, et al.. (2022). A novel machine learning model based on sparse structure learning with adaptive graph regularization for predicting drug side effects. Journal of Biomedical Informatics. 132. 104131–104131. 11 indexed citations

Qu, Lingzhi, Xiaojuan Chen, Hudie Wei, et al.. (2022). Structural insights into the potency and selectivity of covalent pan-FGFR inhibitors. Communications Chemistry. 5(1). 5–5. 17 indexed citations

10.

Jiang, Longying, Hudie Wei, Shuyan Dai, et al.. (2022). Structural insight into the molecular mechanism of cilofexor binding to the farnesoid X receptor. Biochemical and Biophysical Research Communications. 595. 1–6. 5 indexed citations

11.

Qu, Lingzhi, Ming Guo, Huajun Zhang, et al.. (2022). Characterization of the modification of Kelch-like ECH-associated protein 1 by different fumarates. Biochemical and Biophysical Research Communications. 605. 9–15. 7 indexed citations

12.

Dai, Shuyan, Lingzhi Qu, Jun Li, et al.. (2022). Structural insight into the ligand binding mechanism of aryl hydrocarbon receptor. Nature Communications. 13(1). 6234–6234. 37 indexed citations

13.

Qu, Lingzhi, et al.. (2021). Specific emitter identification based on one-dimensional complex-valued residual networks with an attention mechanism. Bulletin of the Polish Academy of Sciences Technical Sciences. 138814–138814. 3 indexed citations

14.

Qu, Lingzhi, et al.. (2021). Specific Emitter Identification Based on Two Residual Networks. 1863–1869. 1 indexed citations

15.

Jiang, Longying, Desheng Xiao, Yubin Li, et al.. (2020). Structural basis of tropifexor as a potent and selective agonist of farnesoid X receptor. Biochemical and Biophysical Research Communications. 534. 1047–1052. 18 indexed citations

16.

Jiang, Longying, Shuyan Dai, Jun Li, et al.. (2019). Structural basis of binding of homodimers of the nuclear receptor NR4A2 to selective Nur-responsive DNA elements. Journal of Biological Chemistry. 294(51). 19795–19803. 25 indexed citations

17.

Wu, Daichao, Lingzhi Qu, Yang Fu, et al.. (2016). Expression and purification of the kinase domain of PINK1 in Pichia pastoris. Protein Expression and Purification. 128. 67–72. 4 indexed citations

18.

Li, Xin, Dawei Deng, Jianpeng Xue, et al.. (2014). Quantum dots based molecular beacons for in vitro and in vivo detection of MMP-2 on tumor. Biosensors and Bioelectronics. 61. 512–518. 75 indexed citations

19.

Deng, Dawei, Jie Cao, Lingzhi Qu, Samuel Achilefu, & Yueqing Gu. (2013). Highly luminescent water-soluble quaternary Zn–Ag–In–S quantum dots for tumor cell-targeted imaging. Physical Chemistry Chemical Physics. 15(14). 5078–5078. 87 indexed citations

20.

Deng, Dawei, Junfei Xia, Jie Cao, et al.. (2011). Forming highly fluorescent near-infrared emitting PbS quantum dots in water using glutathione as surface-modifying molecule. Journal of Colloid and Interface Science. 367(1). 234–240. 49 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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