Kai Huang

2.8k total citations · 1 hit paper
92 papers, 2.1k citations indexed

About

Kai Huang is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Kai Huang has authored 92 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 34 papers in Cancer Research and 31 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Kai Huang's work include Ferroptosis and cancer prognosis (28 papers), Cancer-related molecular mechanisms research (21 papers) and RNA modifications and cancer (15 papers). Kai Huang is often cited by papers focused on Ferroptosis and cancer prognosis (28 papers), Cancer-related molecular mechanisms research (21 papers) and RNA modifications and cancer (15 papers). Kai Huang collaborates with scholars based in China, United States and Portugal. Kai Huang's co-authors include Chunsheng Kang, Chao Yang, Jianwei Wei, Xingen Zhu, Zewei Tu, Chuming Tao, Lei Wu, Qing Hu, Lei Han and Jingying Li and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Energy & Environmental Science.

In The Last Decade

Kai Huang

86 papers receiving 2.0k citations

Hit Papers

Non-coding RNAs as regulators in epigenetics 2016 2026 2019 2022 2016 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kai Huang China 24 1.4k 892 259 240 195 92 2.1k
Leonardo Elia Italy 22 1.7k 1.2× 1.3k 1.5× 272 1.1× 158 0.7× 113 0.6× 31 2.6k
Sergiu Șușman Romania 17 801 0.6× 407 0.5× 200 0.8× 310 1.3× 280 1.4× 58 1.8k
Hailiang Hu China 24 1.3k 0.9× 554 0.6× 209 0.8× 221 0.9× 62 0.3× 73 1.8k
Ling Yu China 31 1.7k 1.2× 661 0.7× 251 1.0× 436 1.8× 233 1.2× 76 2.8k
Boon-Seng Soh Singapore 24 2.4k 1.7× 696 0.8× 132 0.5× 283 1.2× 174 0.9× 48 3.1k
Yuqing Chen China 26 1.4k 1.0× 783 0.9× 176 0.7× 326 1.4× 75 0.4× 80 2.1k
Dorina Veliceasa United States 21 775 0.5× 435 0.5× 202 0.8× 283 1.2× 146 0.7× 28 1.4k
Zhenhong Ni China 21 1.8k 1.3× 849 1.0× 111 0.4× 204 0.8× 147 0.8× 43 2.6k
Francesco Neri Italy 24 2.4k 1.7× 547 0.6× 117 0.5× 240 1.0× 165 0.8× 63 2.9k

Countries citing papers authored by Kai Huang

Since Specialization
Citations

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

Fields of papers citing papers by Kai Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Huang. A scholar is included among the top collaborators of Kai Huang 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 Kai Huang. Kai Huang 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.
Wang, Chong, et al.. (2025). Identification of TAP2 as a novel immune target in human cancers: insights from integrated bioinformatics and experimental approaches. European journal of medical research. 30(1). 163–163. 1 indexed citations
2.
Shen, Dan, Kai Wang, Zhendong Guo, et al.. (2025). Proteomic analysis of dysregulated pulmonary protein expression and potential pathways in broilers induced by particulate matter exposure in poultry houses. Poultry Science. 104(9). 105388–105388. 1 indexed citations
3.
Qian, Bei, Dan Zhou, Feixiang Zhu, et al.. (2025). External stent ameliorates vein graft remodeling through Ajuba-mediated suppression of Hippo signaling pathway. Biomaterials Advances. 177. 214427–214427.
4.
Xu, Pengcheng, Kai Huang, Ren Wang, et al.. (2024). Transforming plant proteins into sustainable food packaging films with enhanced mechanical and preservative properties. Food Hydrocolloids. 162. 110965–110965. 4 indexed citations
5.
Huang, Kai, Dan Pu, Ting Mei, et al.. (2024). Neoadjuvant chemoimmunotherapy in patients with limited-stage small cell lung cancer: A retrospective study.. Journal of Clinical Oncology. 42(16_suppl). e20002–e20002. 2 indexed citations
6.
Deng, Bohan, He Xian, Peng Du, et al.. (2024). PTFE as a Multifunctional Binder for High‐Current‐Density Oxygen Evolution. Advanced Science. 11(41). e2408544–e2408544. 8 indexed citations
7.
Tu, Zewei, Yuyang Huang, Shigang Lv, et al.. (2023). Pan-cancer analysis: predictive role of TAP1 in cancer prognosis and response to immunotherapy. BMC Cancer. 23(1). 133–133. 15 indexed citations
8.
Wu, Wei, et al.. (2023). N6-methyladenosine (m6A)-connected lncRNAs are linked to survival and immune infiltration in glioma patients. Bioscience Reports. 43(5). 3 indexed citations
9.
Tu, Zewei, Xiaolin Wang, Huan Cai, et al.. (2023). The cell senescence regulator p16 is a promising cancer prognostic and immune check-point inhibitor (ICI) therapy biomarker. Aging. 15(6). 2136–2157. 5 indexed citations
10.
Deng, Bohan, Wei Zhao, Yuanzheng Long, et al.. (2023). A self-circulating pathway for the oxygen evolution reaction. Energy & Environmental Science. 16(11). 5210–5219. 58 indexed citations
11.
Xiao, Feng, Xiang Zhou, Yun Guo, et al.. (2023). PPP1R81 correlates with the survival and cell proliferation in lower-grade glioma. Bioscience Reports. 43(5).
12.
Huang, Kai, et al.. (2023). The HNF4A-CHPF pathway promotes proliferation and invasion through interactions with MAD1L1 in glioma. Aging. 15(20). 11052–11066. 2 indexed citations
13.
Lin, Changchun, Weimin Wang, Deyin Zhang, et al.. (2023). Analysis of liver miRNA in Hu sheep with different residual feed intake. Frontiers in Genetics. 14. 1113411–1113411.
14.
Huang, Kai, et al.. (2022). Comprehensive analysis of the prognostic and role in immune cell infiltration of MSR1 expression in lower‐grade gliomas. Cancer Medicine. 11(9). 2020–2035. 11 indexed citations
15.
Tu, Zewei, Jingying Li, Xiaoyan Long, et al.. (2022). Transcriptional Patterns of Lower‐Grade Glioma Patients with Distinct Ferroptosis Levels, Immunotherapy Response, and Temozolomide Sensitivity. Oxidative Medicine and Cellular Longevity. 2022(1). 9408886–9408886. 7 indexed citations
16.
Huang, Kai, et al.. (2019). Non-coding RNAs: Regulators of glioma cell epithelial-mesenchymal transformation. Pathology - Research and Practice. 215(9). 152539–152539. 23 indexed citations
17.
Yang, Chao, Yansheng Li, Qixue Wang, et al.. (2017). EGFR/EGFRvIII remodels the cytoskeleton via epigenetic silencing of AJAP1 in glioma cells. Cancer Letters. 403. 119–127. 17 indexed citations
18.
Chen, Gang, Yan Li, Guoxiong Xu, et al.. (2015). Alteration of ASIC1 expression in clear cell renal cell carcinoma. OncoTargets and Therapy. 8. 2121–2121. 5 indexed citations
19.
Huang, Kai, et al.. (2014). Clinicopathological and cellular signature of PAK1 in human bladder cancer. Tumor Biology. 36(4). 2359–2368. 9 indexed citations
20.
Zhang, Jian-Nan, Kai Huang, Jian Zou, et al.. (2011). High  -catenin/Tcf-4 activity confers glioma progression via direct regulation of AKT2 gene expression. Neuro-Oncology. 13(6). 600–609. 61 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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