Yu‐Qing Ni

790 total citations · 1 hit paper
19 papers, 547 citations indexed

About

Yu‐Qing Ni is a scholar working on Molecular Biology, Cancer Research and Epidemiology. According to data from OpenAlex, Yu‐Qing Ni has authored 19 papers receiving a total of 547 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Cancer Research and 5 papers in Epidemiology. Recurrent topics in Yu‐Qing Ni's work include Cancer-related molecular mechanisms research (7 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers) and RNA regulation and disease (3 papers). Yu‐Qing Ni is often cited by papers focused on Cancer-related molecular mechanisms research (7 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers) and RNA regulation and disease (3 papers). Yu‐Qing Ni collaborates with scholars based in China, Canada and United Kingdom. Yu‐Qing Ni's co-authors include You‐Shuo Liu, Junkun Zhan, Hui Xu, Qunyan Xiang, Chen Li, Jieyu He, Yan Zhao, Shuang Li, Le Liu and Shuang Li and has published in prestigious journals such as Annals of the New York Academy of Sciences, Nutrients and Signal Transduction and Targeted Therapy.

In The Last Decade

Yu‐Qing Ni

17 papers receiving 541 citations

Hit Papers

Roles and mechanisms of exosomal non-coding RNAs in human... 2021 2026 2022 2024 2021 50 100 150 200 250
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.

  1. Roles and mechanisms of exosomal non-coding RNAs in human health and diseases
    2021 277 citations Chen Li, Yu‐Qing Ni et al. Signal Transduction and Targeted Therapy profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu‐Qing Ni China 11 373 243 76 54 53 19 547
Ilaria Floris France 12 402 1.1× 305 1.3× 110 1.4× 32 0.6× 63 1.2× 23 709
Lingyao Zeng Germany 11 309 0.8× 150 0.6× 89 1.2× 66 1.2× 103 1.9× 25 597
Min Cheng China 11 363 1.0× 218 0.9× 77 1.0× 83 1.5× 113 2.1× 27 573
Qilan Ning China 17 379 1.0× 334 1.4× 73 1.0× 48 0.9× 69 1.3× 31 688
Manli Yu China 10 351 0.9× 330 1.4× 102 1.3× 83 1.5× 88 1.7× 15 588
Jichang Zhang China 12 350 0.9× 312 1.3× 43 0.6× 43 0.8× 50 0.9× 34 585
Haiyan Pan China 11 436 1.2× 363 1.5× 60 0.8× 42 0.8× 32 0.6× 25 669
Ming-Hui Zheng China 16 399 1.1× 175 0.7× 67 0.9× 93 1.7× 77 1.5× 32 684
Sherin Bakhashab Saudi Arabia 15 228 0.6× 130 0.5× 91 1.2× 48 0.9× 33 0.6× 38 497
Yanhua Li China 15 345 0.9× 178 0.7× 34 0.4× 32 0.6× 29 0.5× 33 625

Countries citing papers authored by Yu‐Qing Ni

Since Specialization
Citations

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

Fields of papers citing papers by Yu‐Qing Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu‐Qing Ni. 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 Yu‐Qing Ni. The network helps show where Yu‐Qing Ni may publish in the future.

Co-authorship network of co-authors of Yu‐Qing Ni

This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Qing Ni. A scholar is included among the top collaborators of Yu‐Qing Ni 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 Yu‐Qing Ni. Yu‐Qing Ni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
2.
Ni, Yu‐Qing, Junkun Zhan, & You‐Shuo Liu. (2024). Decoding the Multiple Identities and Crosstalk of Organokines in Obesity-Related Type 2 Diabetes Mellitus. Aging and Disease.
3.
Cai, Jing, Yu‐Qing Ni, & You‐Shuo Liu. (2024). Exploring the Frontier: Antisense Long Non-Coding RNAs as Key Regulators in Alzheimer’s Disease. Aging and Disease. 16(4). 1793–1812. 1 indexed citations
4.
5.
Xiang, Qunyan, Hui Xu, Junkun Zhan, et al.. (2023). Association between the Triglyceride-Glucose Index and Vitamin D Status in Type 2 Diabetes Mellitus. Nutrients. 15(3). 639–639. 13 indexed citations
6.
7.
He, Jieyu, Yanjiao Wang, Junkun Zhan, et al.. (2023). Icariin attenuates the calcification of vascular smooth muscle cells through ERα – p38MAPK pathway. Aging Medicine. 6(4). 379–385. 1 indexed citations
8.
Ni, Yu‐Qing, Hui Xu, & You‐Shuo Liu. (2022). Roles of Long Non-coding RNAs in the Development of Aging-Related Neurodegenerative Diseases. Frontiers in Molecular Neuroscience. 15. 844193–844193. 20 indexed citations
9.
Lin, Xiao, Qunyan Xiang, Shuang Li, et al.. (2022). BMF-AS1/BMF Promotes Diabetic Vascular Calcification and Aging both In Vitro and In Vivo. Aging and Disease. 14(1). 170–170. 7 indexed citations
10.
Li, Shuang, Yu‐Qing Ni, Chen Li, et al.. (2022). Long noncoding RNA SNHG1 alleviates high glucose-induced vascular smooth muscle cells calcification/senescence by post-transcriptionally regulating Bhlhe40 and autophagy via Atg10. Journal of Physiology and Biochemistry. 79(1). 83–105. 10 indexed citations
11.
Liu, Le, Yu‐Qing Ni, Junkun Zhan, & You‐Shuo Liu. (2021). The Role of SGLT2 Inhibitors in Vascular Aging. Aging and Disease. 12(5). 1323–1323. 32 indexed citations
12.
Li, Chen, Yu‐Qing Ni, Hui Xu, et al.. (2021). Roles and mechanisms of exosomal non-coding RNAs in human health and diseases. Signal Transduction and Targeted Therapy. 6(1). 383–383. 277 indexed citations breakdown →
13.
Xu, Hui, Yu‐Qing Ni, & You‐Shuo Liu. (2021). Mechanisms of Action of MiRNAs and LncRNAs in Extracellular Vesicle in Atherosclerosis. Frontiers in Cardiovascular Medicine. 8. 733985–733985. 26 indexed citations
14.
Ni, Yu‐Qing & You‐Shuo Liu. (2021). New Insights into the Roles and Mechanisms of Spermidine in Aging and Age-Related Diseases. Aging and Disease. 12(8). 1948–1948. 68 indexed citations
15.
Lin, Xiao, Jia‐Yu Zhong, Shuang Li, et al.. (2020). Adiponectin attenuates the premature senescence of vascular smooth muscle cells induced by high glucose through mTOR signaling pathway. Aging Medicine. 3(3). 178–187. 12 indexed citations
16.
Ni, Yu‐Qing, Junkun Zhan, & You‐Shuo Liu. (2020). Roles and mechanisms of MFG-E8 in vascular aging-related diseases. Ageing Research Reviews. 64. 101176–101176. 33 indexed citations
17.
Zhong, Jia‐Yu, Junkun Zhan, Shuang Li, et al.. (2020). LncRNA‐ES3 inhibition by Bhlhe40 is involved in high glucose–induced calcification/senescence of vascular smooth muscle cells. Annals of the New York Academy of Sciences. 1474(1). 61–72. 26 indexed citations
18.
Tai, Shi, Jianjun Tang, Liang Tang, et al.. (2018). Management and Outcome of Ventricular Septal Rupture Complicating Acute Myocardial Infarction: What Is New in the Era of Percutaneous Intervention?. Cardiology. 141(4). 226–232. 14 indexed citations
19.
Ni, Yu‐Qing, Junnan Tang, Shi Tai, et al.. (2018). [Risk factors for early death in acute myocardial infarction patients complicating with ventricular septal rupture].. PubMed. 46(12). 981–986. 2 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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