Haiyong Gu

1.1k citations
17 papers · 946 indexed · 1 hit paper · h-index 12

Haiyong Gu

17 papers receiving 931 citations

Hit Papers

Genetic variants of miRNA sequences and non–small cell lu...5122008202620142020100200300400500

Peers

Haiyong Gu
Comparison fields: 5 of 83
  • Cancer Research 511
  • Molecular Biology 600
  • Plant Science 156
  • Radiology, Nuclear Medicine and Imaging 92
  • Genetics 89
Replace Nenad Bukvić with:
Nenad Bukvić Italy
Yousef G. Amaar United States
Mingliang Wang China
Thomas M. Vollberg United States
Julia Luther Germany
Chihiro Yamagishi Japan
Yuan Pan China
Zhenhao Qi United States
Masanori Matsushita Japan
Malay Chaklader United States
Haiyong Gu relative to Nenad Bukvić Italy Nenad Bukvić's profile →
Citations per field
00.5×4.3×
Nenad Bukvić · 1×
Citations per year

Countries citing papers authored by Haiyong Gu

Since Specialization
Citations

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

Fields of papers citing papers by Haiyong Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Haiyong Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Haiyong Gu Line = papers co-authored together Haiyong Gu links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 20241
2 202311
3 20227
4 202214
5 20215
6
Antitumor effects of flavokawain-B flavonoid in gemcitabine-resistant lung cancer cells are mediated via mitochondrial-mediated apoptosis, ROS production, cell migration and cell invasion inhibition and blocking of PI3K/AKT Signaling pathway.
202116
7 20201
8 20181
9 201859
10 201571
11
Mitral valve repair versus replacement in patients with rheumatic heart disease.
201324
12 201350
13 201261
14 201224
15 201173
16 201016
17
Genetic variants of miRNA sequences and non–small cell lung cancer survivalbreakdown →
2008512

About Haiyong Gu

Haiyong Gu is a scholar working on Biochemistry, Cancer Research and Plant Science, having authored 17 papers that have together received 946 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Rice Cultivation and Yield Improvement (3 papers), Cancer-related molecular mechanisms research (3 papers), Photosynthetic Processes and Mechanisms (2 papers), Esophageal and GI Pathology (2 papers), Laser Applications in Dentistry and Medicine (2 papers) and Bone Tissue Engineering Materials (1 paper). The work is most often cited by research in Cancer Research (511 citations), Molecular Biology (600 citations) and Plant Science (156 citations). Haiyong Gu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zhibin Hu, Hongbing Shen, Hongxia Ma, Jiaping Chen, Guangfu Jin, Lin Xu, Xiaoyi Zhou, Ruifen Miao, Yijiang Chen and Yi Zeng. Their work appears in journals such as Journal of Clinical Investigation, Genetics and FEBS Letters.

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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