Jia Qu

2.4k total citations · 1 hit paper
56 papers, 1.9k citations indexed

About

Jia Qu is a scholar working on Molecular Biology, Cancer Research and Ophthalmology. According to data from OpenAlex, Jia Qu has authored 56 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 20 papers in Cancer Research and 7 papers in Ophthalmology. Recurrent topics in Jia Qu's work include MicroRNA in disease regulation (15 papers), Cancer-related molecular mechanisms research (14 papers) and Circular RNAs in diseases (11 papers). Jia Qu is often cited by papers focused on MicroRNA in disease regulation (15 papers), Cancer-related molecular mechanisms research (14 papers) and Circular RNAs in diseases (11 papers). Jia Qu collaborates with scholars based in China, United States and Japan. Jia Qu's co-authors include Xing Chen, Jianqiang Li, Na‐Na Guan, Jun Yin, Lei Wang, Yazhou Sun, Huang Li, Yan Zhao, Xing Chen and Zhong Ming and has published in prestigious journals such as Journal of Biological Chemistry, Bioinformatics and PLoS ONE.

In The Last Decade

Jia Qu

51 papers receiving 1.9k 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.

Predicting miRNA–disease association based on inductive matrix completion

2018 404 citations Xing Chen, Jia Qu et al. profile →

Peers

Jia Qu

MB

CR

CTM

OPHTH

EPIDE

Rency S. Varghese United States

Shaopeng Wang China

Simon Cockell United Kingdom

Gürkan Bebek United States

Juan Ding China

Jennifer J. Young United States

Konstantinos Sidiropoulos United Kingdom

Chunquan Li China

Chun-Chi Liu Taiwan

Xiaohong Jing United States

Rency S. Varghese United States

Jia Qu

1.4k ×0.9

MB

325 ×0.3

CR

48 ×0.2

CTM

74 ×0.6

OPHTH

282 ×2.6

EPIDE

Citations per year, relative to Jia Qu Jia Qu (= 1×) peers Rency S. Varghese

Countries citing papers authored by Jia Qu

Since Specialization

Citations

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

Fields of papers citing papers by Jia Qu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jia Qu

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

Song, Shuangbao, et al.. (2024). Improving the artificial bee colony algorithm with a proprietary estimation of distribution mechanism for protein–ligand docking. Applied Soft Computing. 161. 111732–111732. 3 indexed citations

2.

Song, Shuangbao, et al.. (2023). Wart-Treatment Efficacy Prediction Using a CMA-ES-Based Dendritic Neuron Model. Applied Sciences. 13(11). 6542–6542. 3 indexed citations

3.

Qu, Jia, et al.. (2023). A new integrated framework for the identification of potential virus–drug associations. Frontiers in Microbiology. 14. 1179414–1179414. 5 indexed citations

4.

Hou, Zhenjie, et al.. (2023). Prediction of potential drug-microbe associations based on matrix factorization and a three-layer heterogeneous network. Computational Biology and Chemistry. 104. 107857–107857. 5 indexed citations

5.

Qu, Jia, et al.. (2022). Neighborhood-based inference and restricted Boltzmann machine for microbe and drug associations prediction. PeerJ. 10. e13848–e13848. 9 indexed citations

6.

Qu, Jia, et al.. (2021). Biased Random Walk With Restart on Multilayer Heterogeneous Networks for MiRNA–Disease Association Prediction. Frontiers in Genetics. 12. 720327–720327. 8 indexed citations

7.

Chen, Xing, Jia Qu, & Jun Yin. (2018). TLHNMDA: Triple Layer Heterogeneous Network Based Inference for MiRNA-Disease Association Prediction. Frontiers in Genetics. 9. 234–234. 24 indexed citations

8.

Guo, Dongqing, Colin E. Murdoch, Tianhua Liu, et al.. (2018). Therapeutic Angiogenesis of Chinese Herbal Medicines in Ischemic Heart Disease: A Review. Frontiers in Pharmacology. 9. 428–428. 37 indexed citations

9.

Qu, Jia, Xing Chen, Yazhou Sun, Jianqiang Li, & Zhong Ming. (2018). Inferring potential small molecule–miRNA association based on triple layer heterogeneous network. Journal of Cheminformatics. 10(1). 30–30. 70 indexed citations

10.

Qu, Jia, Xing Chen, Yazhou Sun, et al.. (2018). In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm. Molecular Therapy — Nucleic Acids. 14. 274–286. 46 indexed citations

11.

Chen, Xing, Jun Yin, Jia Qu, & Huang Li. (2018). MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction. PLoS Computational Biology. 14(8). e1006418–e1006418. 309 indexed citations

12.

Zhang, Dongda, Nan Jin, Wei Sun, et al.. (2016). Phosphoglycerate mutase 1 promotes cancer cell migration independent of its metabolic activity. Oncogene. 36(20). 2900–2909. 72 indexed citations

13.

Zhang, Hongxing, Na Huang, Kun‐Chao Wu, et al.. (2014). Comprehensive Molecular Diagnosis of Bardet-Biedl Syndrome by High-Throughput Targeted Exome Sequencing. PLoS ONE. 9(3). e90599–e90599. 28 indexed citations

14.

Shen, Meixiao, et al.. (2013). Interocular Evaluation of Axial Length and Retinal Thickness in People With Myopic Anisometropia. Eye & Contact Lens Science & Clinical Practice. 39(4). 277–282. 16 indexed citations

15.

Zhang, Zongduan, et al.. (2012). Clinicopathological Features and Surgical Treatment of Intratarsal Keratinous Cysts. American Journal of Dermatopathology. 35(1). 78–82. 8 indexed citations

16.

Ji, Yanchun, Xiaoling Liu, Fuxin Zhao, et al.. (2011). The mitochondrial ND5 T12338C mutation may be associ-ated with Leber’s hereditary optic neuropathy in two Chinese fami-lies. Hereditas (Beijing). 33(4). 322–328. 2 indexed citations

17.

Zhang, Yongmei, Yanchun Ji, Xiaoling Liu, et al.. (2010). Leber's hereditary optic neuropathy may be associated with the mitochondrial tRNAGlu A14693G mutation in three Chinese families. Hereditas (Beijing). 32(4). 353–359. 2 indexed citations

18.

Liu, Yan, Yi Tong, Jia Qu, et al.. (2010). Leber's hereditary optic neuropathy and limbs abnormity claudication may be associated with the mitochondrial ND1 T3866C mutation. Hereditas (Beijing). 32(2). 141–147. 1 indexed citations

19.

Li, Wensheng, Fansheng Kong, Xia Li, et al.. (2009). Gene therapy following subretinal AAV5 vector delivery is not affected by a previous intravitreal AAV5 vector administration in the partner eye.. PubMed. 15. 267–75. 43 indexed citations

20.

Wang, Zhaoyang, Keke Zhao, Zongming Song, Lijun Shen, & Jia Qu. (2009). Erythropoietin as a novel therapeutic agent for atrophic age-related macular degeneration. Medical Hypotheses. 72(4). 448–450. 10 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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