Yu Kang

2.6k total citations · 1 hit paper
76 papers, 1.6k citations indexed

About

Yu Kang is a scholar working on Molecular Biology, Epidemiology and Oncology. According to data from OpenAlex, Yu Kang has authored 76 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 12 papers in Epidemiology and 9 papers in Oncology. Recurrent topics in Yu Kang's work include Genomics and Phylogenetic Studies (10 papers), Gut microbiota and health (9 papers) and RNA and protein synthesis mechanisms (8 papers). Yu Kang is often cited by papers focused on Genomics and Phylogenetic Studies (10 papers), Gut microbiota and health (9 papers) and RNA and protein synthesis mechanisms (8 papers). Yu Kang collaborates with scholars based in China, United States and Australia. Yu Kang's co-authors include Yixiang Han, Shenghui Zhang, Jianbo Wu, Jun Yu, Xing Shi, Zhancheng Gao, Songfu Jiang, Xi Xu, Lufeng Ren and Ying Liang and has published in prestigious journals such as Nature, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Yu Kang

75 papers receiving 1.6k citations

Hit Papers

Farmed fur animals harbou... 2024 2026 2024 10 20 30
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. Farmed fur animals harbour viruses with zoonotic spillover potential
    2024 36 citations Jin Zhao, Yu Kang et al. Nature 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 Kang China 22 785 302 258 217 202 76 1.6k
Chao Zhao China 27 1.2k 1.5× 291 1.0× 643 2.5× 149 0.7× 346 1.7× 89 2.5k
Bahtiyar Yılmaz Switzerland 24 1.6k 2.0× 500 1.7× 424 1.6× 423 1.9× 154 0.8× 63 2.8k
Vu Nguyen United States 18 1.5k 1.8× 820 2.7× 213 0.8× 268 1.2× 207 1.0× 35 2.7k
Dalin Li United States 19 672 0.9× 488 1.6× 402 1.6× 365 1.7× 110 0.5× 67 1.8k
Lulu Sun China 17 835 1.1× 266 0.9× 266 1.0× 348 1.6× 199 1.0× 66 1.6k
Xuhui Zhu China 23 697 0.9× 417 1.4× 165 0.6× 171 0.8× 95 0.5× 58 1.7k
Aiping Zhao United States 32 723 0.9× 851 2.8× 282 1.1× 308 1.4× 137 0.7× 79 2.9k
Wentao Ma China 24 1.3k 1.7× 447 1.5× 320 1.2× 291 1.3× 135 0.7× 96 2.7k
Laura Coughlin United States 11 1.0k 1.3× 168 0.6× 150 0.6× 443 2.0× 439 2.2× 26 1.4k

Countries citing papers authored by Yu Kang

Since Specialization
Citations

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

Fields of papers citing papers by Yu Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Kang. A scholar is included among the top collaborators of Yu Kang 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 Kang. Yu Kang 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.
Zhang, Yixue, Jialu Wu, Yu Kang, & Tingjun Hou. (2025). A multimodal contrastive learning framework for predicting P-glycoprotein substrates and inhibitors. Journal of Pharmaceutical Analysis. 15(8). 101313–101313. 1 indexed citations
2.
Huang, Zhuo, Yukun He, Yu Kang, et al.. (2024). Enhancing Variant Calling in Whole-exome Sequencing Data Using Population-matched Reference Genomes. Genomics Proteomics & Bioinformatics. 22(5). 1 indexed citations
3.
Kang, Yu, Huan Zhao, Ningshao Xia, et al.. (2024). Oncolytic activity of a coxsackievirus B3 strain in patient-derived cervical squamous cell carcinoma organoids and synergistic effect with paclitaxel. Virology Journal. 21(1). 245–245. 1 indexed citations
4.
Kang, Yu, et al.. (2024). Characterization of Escherichia coli as a Recombinant Protein Expression Host and its Optimization. Academic Journal of Science and Technology. 12(2). 223–225. 1 indexed citations
5.
Zhao, Jin, Yu Kang, Philippe Lemey, et al.. (2024). Farmed fur animals harbour viruses with zoonotic spillover potential. Nature. 634(8032). 228–233. 36 indexed citations breakdown →
6.
7.
8.
Luo, Zhouqing, Yu Kang, Shuang Xie, et al.. (2021). Compacting a synthetic yeast chromosome arm. Genome biology. 22(1). 5–5. 24 indexed citations
9.
Zheng, Mingxia, et al.. (2020). Cardiac tamponade complicating thoracentesis in a patient after left pneumonectomy. Medicine. 99(15). e19778–e19778. 1 indexed citations
10.
Dong, Yuqing, Yixiang Han, Songfu Jiang, et al.. (2020). PD-L1 Is Expressed and Promotes the Expansion of Regulatory T Cells in Acute Myeloid Leukemia. Frontiers in Immunology. 11. 1710–1710. 68 indexed citations
11.
Shi, Xing, Zhancheng Gao, Qiang Lin, et al.. (2019). Meta-Analysis Reveals Potential Influence of Oxidative Stress on the Airway Microbiomes of Cystic Fibrosis Patients. Genomics Proteomics & Bioinformatics. 17(6). 590–602. 4 indexed citations
12.
Han, Yixiang, Yifen Shi, Wanling Xu, et al.. (2018). Benzene induces haematotoxicity by promoting deacetylation and autophagy. Journal of Cellular and Molecular Medicine. 23(2). 1022–1033. 26 indexed citations
13.
Pu, Ning, Yali Zheng, Xiaohui Liu, et al.. (2018). Metabolic profiles in community-acquired pneumonia: developing assessment tools for disease severity. Critical Care. 22(1). 130–130. 48 indexed citations
14.
Huang, Yichen, Xing Shi, Zhiyong Li, et al.. (2018). Possible association of Firmicutes in the gut microbiota of patients with major depressive disorder. Neuropsychiatric Disease and Treatment. Volume 14. 3329–3337. 238 indexed citations
15.
Zhao, Yongbing, Chen Sun, Dongyu Zhao, et al.. (2018). PGAP-X: extension on pan-genome analysis pipeline. BMC Genomics. 19(S1). 36–36. 26 indexed citations
16.
Yuan, Lina, Yang Yu, Yanmin Zhu, et al.. (2017). GAAP: Genome-organization-framework-Assisted Assembly Pipeline for prokaryotic genomes. BMC Genomics. 18(S1). 952–952. 6 indexed citations
17.
Li, Jiaqi, Songfu Jiang, Yi Chen, et al.. (2017). Benzene metabolite hydroquinone induces apoptosis of bone marrow mononuclear cells through inhibition of β-catenin signaling. Toxicology in Vitro. 46. 361–369. 20 indexed citations
18.
Bi, Laixi, Junqing Wu, Jianbo Wu, et al.. (2016). Increased Th17 cells and IL-17A exist in patients with B cell acute lymphoblastic leukemia and promote proliferation and resistance to daunorubicin through activation of Akt signaling. Journal of Translational Medicine. 14(1). 132–132. 25 indexed citations
19.
Zhu, Lingxiang, Jun Zhong, Xinmiao Jia, et al.. (2015). Precision methylome characterization ofMycobacterium tuberculosiscomplex (MTBC) using PacBio single-molecule real-time (SMRT) technology. Nucleic Acids Research. 44(2). 730–743. 79 indexed citations
20.
Li, Dezhi, Yanan Chu, Lufeng Ren, et al.. (2013). Complete genome sequence of methicillin-sensitive Staphylococcus aureus containing a heterogeneic staphylococcal cassette chromosome element. Science China Life Sciences. 56(3). 268–274.

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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