Bei Li

1.4k total citations · 1 hit paper
46 papers, 848 citations indexed

About

Bei Li is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Bei Li has authored 46 papers receiving a total of 848 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 20 papers in Cancer Research and 10 papers in Genetics. Recurrent topics in Bei Li's work include Cancer-related molecular mechanisms research (12 papers), MicroRNA in disease regulation (10 papers) and Circular RNAs in diseases (8 papers). Bei Li is often cited by papers focused on Cancer-related molecular mechanisms research (12 papers), MicroRNA in disease regulation (10 papers) and Circular RNAs in diseases (8 papers). Bei Li collaborates with scholars based in China, United States and Switzerland. Bei Li's co-authors include Si Sun, Qi Wu, Juanjuan Li, Zhiyu Li, Shengrong Sun, Manglai Dugarjaviin, Yiping Zhao, Dongyi Bai, Xiaolong He and Xinzhuang Zhang and has published in prestigious journals such as The Journal of Experimental Medicine, PLoS ONE and Scientific Reports.

In The Last Decade

Bei Li

43 papers receiving 839 citations

Hit Papers

Cancer-associated adipocytes: key players in breast cance... 2019 2026 2021 2023 2019 100 200 300
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. Cancer-associated adipocytes: key players in breast cancer progression
    2019 334 citations Qi Wu, Bei Li et al. Journal of Hematology & Oncology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bei Li China 15 482 304 174 99 87 46 848
Deshun Shi China 15 560 1.2× 241 0.8× 107 0.6× 45 0.5× 50 0.6× 84 910
Hong Chang China 20 593 1.2× 306 1.0× 154 0.9× 89 0.9× 96 1.1× 85 1.2k
Chi‐Ming Liang Taiwan 19 387 0.8× 203 0.7× 148 0.9× 221 2.2× 83 1.0× 31 942
Peng Yuan China 17 831 1.7× 273 0.9× 83 0.5× 125 1.3× 77 0.9× 53 1.3k
Kyle M. Schachtschneider United States 19 539 1.1× 173 0.6× 203 1.2× 128 1.3× 59 0.7× 52 1.1k
Farshad Niazi United States 12 579 1.2× 370 1.2× 111 0.6× 100 1.0× 50 0.6× 15 868
Shudai Lin China 16 428 0.9× 231 0.8× 77 0.4× 61 0.6× 30 0.3× 48 777
Alfonso Lavorgna United States 14 350 0.7× 232 0.8× 111 0.6× 355 3.6× 65 0.7× 19 762
義夫 田中 China 17 685 1.4× 242 0.8× 122 0.7× 281 2.8× 68 0.8× 29 1.1k

Countries citing papers authored by Bei Li

Since Specialization
Citations

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

Fields of papers citing papers by Bei Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bei Li

This figure shows the co-authorship network connecting the top 25 collaborators of Bei Li. A scholar is included among the top collaborators of Bei Li 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 Bei Li. Bei Li 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, Lei, et al.. (2025). The effect of resveratrol on the cryopreservation of Mongolian horse semen. Archives animal breeding/Archiv für Tierzucht. 68(1). 27–41. 1 indexed citations
2.
3.
Wang, Ping, Fang Zhou, Wei Pei, et al.. (2024). Senescence Reprogramming by MTHFD2 Deficiency Facilitates Tumor Progression. Journal of Cancer. 15(20). 6577–6593. 1 indexed citations
4.
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Zhao, Xue, Xin Song, Rui‐Hua Xu, et al.. (2024). Novel metabolic biomarker for early detection and diagnosis to the patients with gastric cardia adenocarcinoma. Cancer Medicine. 13(5). e7015–e7015. 5 indexed citations
6.
Fei, Dongdong, Yazheng Wang, Qiming Zhai, et al.. (2021). KAT6A regulates stemness of aging bone marrow-derived mesenchymal stem cells through Nrf2/ARE signaling pathway. Stem Cell Research & Therapy. 12(1). 104–104. 23 indexed citations
7.
Pan, Qingchun, et al.. (2021). LncRNA THAP9-AS1 accelerates cell growth of esophageal squamous cell carcinoma through sponging miR-335–5p to regulate SGMS2. Pathology - Research and Practice. 224. 153526–153526. 12 indexed citations
8.
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Zhao, Yiping, Guiqin Liu, Dongyi Bai, et al.. (2020). Characterization and comparison of the bacterial microbiota in different gastrointestinal tract compartments of Mongolian horses. MicrobiologyOpen. 9(6). 1085–1101. 29 indexed citations
10.
Wu, Yihan, Yiping Zhao, Bei Li, et al.. (2020). Hair follicle regional specificity in different parts of bay Mongolian horse by histology and transcriptional profiling. BMC Genomics. 21(1). 651–651. 2 indexed citations
11.
Li, Bei, et al.. (2019). miR‐636 represses cell survival by targeting CDK6/Bcl‐2 in cervical cancer. The Kaohsiung Journal of Medical Sciences. 36(5). 328–335. 23 indexed citations
12.
Wu, Qi, Bei Li, Zhiyu Li, et al.. (2019). Cancer-associated adipocytes: key players in breast cancer progression. Journal of Hematology & Oncology. 12(1). 95–95. 334 indexed citations breakdown →
13.
Yang, Shengzhi, Jianghong Meng, Anyun Zhang, et al.. (2018). Metagenomic Analysis of Bacteria, Fungi, Bacteriophages, and Helminths in the Gut of Giant Pandas. Frontiers in Microbiology. 9. 1717–1717. 44 indexed citations
14.
Wang, Xisheng, et al.. (2017). Association analysis between major temperament traits and diversification of the candidate gene in Mongolian horse (Equus caballus).. Journal of Pharmaceutical and Biomedical Sciences. 25(3). 405–414. 1 indexed citations
15.
Li, Bei, et al.. (2017). Progress in the whole genome of Equus by using high-throughput sequencing technologies. 39(11). 974–983. 2 indexed citations
16.
Li, Bei, et al.. (2017). Regulatory pathway analysis of coat color genes in Mongolian horses. Hereditas. 155(1). 13–13. 6 indexed citations
17.
Huang, Sai, Xuan Zhou, Bei Li, et al.. (2017). Identification of miRNA biomarkers of pneumonia using RNA-sequencing and bioinformatics analysis. Experimental and Therapeutic Medicine. 13(4). 1235–1244. 28 indexed citations
18.
Hruška-Plocháň, Marián, Bei Li, Diego Kyburz, et al.. (2015). New and emerging roles of small RNAs in neurodegeneration, muscle, cardiovascular and inflammatory diseases. Swiss Medical Weekly. 145(3738). w14192–w14192. 12 indexed citations
19.
20.
Zhao, Yiping, Bei Li, Dongyi Bai, et al.. (2015). Comparison of Fecal Microbiota of Mongolian and Thoroughbred Horses by High-throughput Sequencing of the V4 Region of the 16S rRNA Gene. Asian-Australasian Journal of Animal Sciences. 29(9). 1345–1352. 40 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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