Ku-Geng Huo

634 total citations
13 papers, 425 citations indexed

About

Ku-Geng Huo is a scholar working on Molecular Biology, Cancer Research and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Ku-Geng Huo has authored 13 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Cancer Research and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Ku-Geng Huo's work include MicroRNA in disease regulation (4 papers), Circular RNAs in diseases (3 papers) and Atherosclerosis and Cardiovascular Diseases (3 papers). Ku-Geng Huo is often cited by papers focused on MicroRNA in disease regulation (4 papers), Circular RNAs in diseases (3 papers) and Atherosclerosis and Cardiovascular Diseases (3 papers). Ku-Geng Huo collaborates with scholars based in Canada, France and China. Ku-Geng Huo's co-authors include Júlio C Fraulob-Aquino, Ming‐Sound Tsao, Ernesto L. Schiffrin, Pierre Paradis, Elisa D’Arcangelo, Sofiane Ouerd, Tlili Barhoumi, Antoine Caillon, Muhammad Oneeb Rehman Mian and Peter Sinnaeve and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Hypertension.

In The Last Decade

Ku-Geng Huo

13 papers receiving 423 citations

Peers

Ku-Geng Huo
Ku-Geng Huo
Citations per year, relative to Ku-Geng Huo Ku-Geng Huo (= 1×) peers Guili Lian

Countries citing papers authored by Ku-Geng Huo

Since Specialization
Citations

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

Fields of papers citing papers by Ku-Geng Huo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ku-Geng Huo. 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 Ku-Geng Huo. The network helps show where Ku-Geng Huo may publish in the future.

Co-authorship network of co-authors of Ku-Geng Huo

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

All Works

13 of 13 papers shown
1.
Liu, Huaqing, et al.. (2024). PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery. Scientific Data. 11(1). 1316–1316. 5 indexed citations
2.
Berillo, Olga, Ku-Geng Huo, Chantal Richer, et al.. (2022). Distinct transcriptomic profile of small arteries of hypertensive patients with chronic kidney disease identified miR-338-3p targeting GPX3 and PTPRS. Journal of Hypertension. 40(7). 1394–1405. 5 indexed citations
3.
Huo, Ku-Geng, Hirotsugu Notsuda, Zhenhao Fang, et al.. (2021). Lung Cancer Driven by BRAFG469V Mutation Is Targetable by EGFR Kinase Inhibitors. Journal of Thoracic Oncology. 17(2). 277–288. 21 indexed citations
4.
Fang, Zhenhao, Ki‐Young Lee, Ku-Geng Huo, et al.. (2020). Multivalent assembly of KRAS with the RAS-binding and cysteine-rich domains of CRAF on the membrane. Proceedings of the National Academy of Sciences. 117(22). 12101–12108. 50 indexed citations
5.
Huo, Ku-Geng, Elisa D’Arcangelo, & Ming‐Sound Tsao. (2020). Patient-derived cell line, xenograft and organoid models in lung cancer therapy. Translational Lung Cancer Research. 9(5). 2214–2232. 67 indexed citations
6.
Berillo, Olga, Ku-Geng Huo, Júlio C Fraulob-Aquino, et al.. (2020). Circulating let-7g-5p and miR-191-5p Are Independent Predictors of Chronic Kidney Disease in Hypertensive Patients. American Journal of Hypertension. 33(6). 505–513. 19 indexed citations
7.
Huo, Ku-Geng, Chantal Richer, Olga Berillo, et al.. (2019). miR-431-5p Knockdown Protects Against Angiotensin II–Induced Hypertension and Vascular Injury. Hypertension. 73(5). 1007–1017. 22 indexed citations
8.
Paradis, Pierre, Ku-Geng Huo, Chantal Richer, et al.. (2018). A2935 microRNA profiling in peripheral blood mononuclear cells from hypertensive patients with or without chronic kidney disease. Journal of Hypertension. 36. e21–e21. 1 indexed citations
9.
Caillon, Antoine, Muhammad Oneeb Rehman Mian, Júlio C Fraulob-Aquino, et al.. (2017). γδ T Cells Mediate Angiotensin II-Induced Hypertension and Vascular Injury. Circulation. 135(22). 2155–2162. 142 indexed citations
10.
Barhoumi, Tlili, Júlio C Fraulob-Aquino, Muhammad Oneeb Rehman Mian, et al.. (2017). Matrix metalloproteinase-2 knockout prevents angiotensin II-induced vascular injury. Cardiovascular Research. 113(14). 1753–1762. 56 indexed citations
11.
Caillon, Antoine, Muhammad Oneeb Rehman Mian, Júlio C Fraulob-Aquino, et al.. (2016). PS 07-28 GAMMA/DELTA T CELLS MEDIATE ANGIOTENSIN II-INDUCED HYPERTENSION AND VASCULAR INJURY. Journal of Hypertension. 34(Supplement 1). e290–e290. 1 indexed citations
12.
Rautureau, Yohann, Júlio C Fraulob-Aquino, Ku-Geng Huo, et al.. (2015). Inducible Human Endothelin-1 Overexpression in Endothelium Raises Blood Pressure via Endothelin Type A Receptors. Hypertension. 66(2). 347–355. 33 indexed citations
13.
Huo, Ku-Geng, et al.. (1993). A stable vector for high-level expression and secretion of human interferon alpha A in yeast.. PubMed. 36(5). 557–67. 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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