Hui Ling

8.2k total citations · 1 hit paper
125 papers, 5.0k citations indexed

About

Hui Ling is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Hui Ling has authored 125 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Molecular Biology, 37 papers in Cancer Research and 19 papers in Oncology. Recurrent topics in Hui Ling's work include Cancer-related molecular mechanisms research (27 papers), MicroRNA in disease regulation (22 papers) and Circular RNAs in diseases (15 papers). Hui Ling is often cited by papers focused on Cancer-related molecular mechanisms research (27 papers), MicroRNA in disease regulation (22 papers) and Circular RNAs in diseases (15 papers). Hui Ling collaborates with scholars based in China, United States and Austria. Hui Ling's co-authors include George A. Călin, Muller Fabbri, Martin Pichler, Masahisa Ohtsuka, Shi‐Wu Chen, Ioana Berindan‐Neagoe, Riccardo Fodde, Yaochun Zhang, Frank J. Slack and Ken R. Vincent and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Hui Ling

121 papers receiving 4.9k citations

Hit Papers

MicroRNAs and other non-coding RNAs as targets for antica... 2013 2026 2017 2021 2013 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hui Ling China 36 3.4k 2.6k 717 335 316 125 5.0k
Chiao‐Wen Lin Taiwan 39 2.7k 0.8× 1.4k 0.5× 905 1.3× 273 0.8× 449 1.4× 176 4.4k
Matilde E. Lleonart Spain 38 3.7k 1.1× 1.8k 0.7× 1.3k 1.8× 428 1.3× 339 1.1× 86 5.6k
Naihan Xu China 36 3.1k 0.9× 1.2k 0.5× 789 1.1× 671 2.0× 274 0.9× 83 4.3k
Yoshihito Nakagawa Japan 35 3.5k 1.0× 2.3k 0.9× 429 0.6× 184 0.5× 264 0.8× 146 5.1k
Alexandru Irimie Romania 29 2.1k 0.6× 1.2k 0.5× 755 1.1× 260 0.8× 304 1.0× 130 3.8k
Xian‐Jun Qu China 37 2.1k 0.6× 987 0.4× 943 1.3× 372 1.1× 550 1.7× 133 3.9k
Dan A. Dixon United States 40 4.2k 1.2× 1.5k 0.6× 710 1.0× 282 0.8× 661 2.1× 92 6.6k
Ping Ji United States 31 4.0k 1.2× 2.6k 1.0× 754 1.1× 256 0.8× 321 1.0× 95 5.1k
Manoj Garg India 39 2.4k 0.7× 990 0.4× 668 0.9× 300 0.9× 570 1.8× 100 3.9k
Alexander T.H. Wu Taiwan 40 2.6k 0.8× 1.1k 0.4× 1.1k 1.6× 292 0.9× 484 1.5× 170 5.1k

Countries citing papers authored by Hui Ling

Since Specialization
Citations

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

Fields of papers citing papers by Hui Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hui Ling

This figure shows the co-authorship network connecting the top 25 collaborators of Hui Ling. A scholar is included among the top collaborators of Hui Ling 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 Hui Ling. Hui Ling 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.
Zeng, Tiebing, et al.. (2026). Mechanistic insights and therapeutic potential of E3 ubiquitin ligases in gastric cancer development. Biochemical and Biophysical Research Communications. 803. 153340–153340.
2.
Wang, Yuhang, et al.. (2025). Preparation and radon exhalation characteristics of fracture granite similar materials in Beishan underground research laboratory. Journal of Hazardous Materials. 487. 137121–137121.
3.
Yin, Zhe, Chuan Zhang, Rui Dong, et al.. (2024). Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations. European journal of medical research. 29(1). 540–540.
4.
Ma, Shaocheng, Junyi Ma, Xuemei Zhang, et al.. (2023). Lappaconitine sulfate inhibits proliferation and induces mitochondrial-mediated apoptosis via regulating PI3K/AKT/GSK3β signaling pathway in HeLa cells. Naunyn-Schmiedeberg s Archives of Pharmacology. 396(12). 3695–3705. 2 indexed citations
5.
Zhang, Chuan, et al.. (2023). Novel de novo mutation in ZBTB20 in a Chinese Primrose syndrome family and a review of the literature. Molecular Genetics & Genomic Medicine. 12(1). e2304–e2304. 1 indexed citations
8.
Lin, Xiaojun, Ling Zhou, Xiaoying Dong, et al.. (2018). Colonic epithelial mTORC1 promotes ulcerative colitis through COX-2-mediated Th17 responses. Mucosal Immunology. 11(6). 1663–1673. 44 indexed citations
9.
Gulei, Diana, Nikolay Mehterov, Hui Ling, et al.. (2017). The “good-cop bad-cop” TGF-beta role in breast cancer modulated by non-coding RNAs. Biochimica et Biophysica Acta (BBA) - General Subjects. 1861(7). 1661–1675. 38 indexed citations
10.
Pichler, Martin, Verena Stiegelbauer, Petra Vychytilova‐Faltejskova, et al.. (2016). Genome-Wide miRNA Analysis Identifies miR-188-3p as a Novel Prognostic Marker and Molecular Factor Involved in Colorectal Carcinogenesis. Clinical Cancer Research. 23(5). 1323–1333. 61 indexed citations
11.
Ling, Hui, et al.. (2016). Non-coding RNAs: the cancer genome dark matter that matters!. Clinical Chemistry and Laboratory Medicine (CCLM). 55(5). 705–714. 53 indexed citations
12.
Ling, Hui, Paloma del C. Monroig, Maria Ciccone, et al.. (2015). Design of a miRNA sponge for the miR-17 miRNA family as a therapeutic strategy against vulvar carcinoma. Molecular and Cellular Probes. 29(6). 420–426. 19 indexed citations
13.
Wang, Meiliang, et al.. (2015). Kinetics and Immunodominance of Virus-Specific T Cell Responses During Hantaan Virus Infection. Viral Immunology. 28(5). 265–271. 9 indexed citations
14.
Ress, Anna Lena, Verena Stiegelbauer, Elke Winter, et al.. (2014). MiR‐96‐5p influences cellular growth and is associated with poor survival in colorectal cancer patients. Molecular Carcinogenesis. 54(11). 1442–1450. 68 indexed citations
15.
Kang, Myoung Hee, et al.. (2014). The prognostic impact of the neutrophil-to-lymphocyte ratio in patients with small-cell lung cancer. British Journal of Cancer. 111(3). 452–460. 165 indexed citations
16.
Ling, Hui, et al.. (2014). Diallyl disulfide selectively causes checkpoint kinase-1 mediated G2/M arrest in human MGC803 gastric cancer cell line. Oncology Reports. 32(5). 2274–2282. 20 indexed citations
17.
Chen, Shi‐Wu, Jie Liu, Wenting Huang, et al.. (2011). Carbamates of 4′-demethyl-4-deoxypodophyllotoxin: Synthesis, cytotoxicity and cell cycle effects. Bioorganic & Medicinal Chemistry Letters. 21(24). 7355–7358. 21 indexed citations
18.
Tan, Hui, Hui Ling, Jie He, et al.. (2008). Inhibition of ERK and activation of p38 are involved in diallyl disulfide induced apoptosis of leukemia HL-60 cells. Archives of Pharmacal Research. 31(6). 786–793. 26 indexed citations
19.
Samant, Sadhana, Hui Ling, Jing Lü, et al.. (2005). The mouse t complex distorter/sterility candidate, Dnahc8, expresses a γ-type axonemal dynein heavy chain isoform confined to the principal piece of the sperm tail. Developmental Biology. 285(1). 57–69. 9 indexed citations
20.
Ling, Hui, et al.. (2003). Inhibitory effect of diallyl disulfide on human gastric cancer cell line MGC803 in vitro. Zhongguo yaolixue tongbao. 3 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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