Weihao Kong

1.6k total citations
48 papers, 783 citations indexed

About

Weihao Kong is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Weihao Kong has authored 48 papers receiving a total of 783 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 14 papers in Cancer Research and 12 papers in Oncology. Recurrent topics in Weihao Kong's work include Ferroptosis and cancer prognosis (6 papers), Cancer-related molecular mechanisms research (6 papers) and Inflammatory Biomarkers in Disease Prognosis (5 papers). Weihao Kong is often cited by papers focused on Ferroptosis and cancer prognosis (6 papers), Cancer-related molecular mechanisms research (6 papers) and Inflammatory Biomarkers in Disease Prognosis (5 papers). Weihao Kong collaborates with scholars based in China, United States and Germany. Weihao Kong's co-authors include Wu-Jun Li, Xingyu Wang, Minyi Guo, Yuanyuan He, Guoqiang Yin, Zhixi Chen, Huabing Zhang, Rongqiang Liu, Mingwei Yang and Honghai Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Frontiers in Immunology.

In The Last Decade

Weihao Kong

44 papers receiving 775 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weihao Kong China 14 279 181 161 131 104 48 783
Ji Hyung Hong South Korea 17 164 0.6× 209 1.2× 274 1.7× 159 1.2× 150 1.4× 59 920
Faisal Azam Saudi Arabia 13 79 0.3× 176 1.0× 393 2.4× 90 0.7× 88 0.8× 43 908
Yasuyuki Sato Japan 17 99 0.4× 239 1.3× 182 1.1× 190 1.5× 87 0.8× 79 941
Weijia Cai China 18 159 0.6× 720 4.0× 260 1.6× 142 1.1× 99 1.0× 44 1.3k
Tokiya Abe Japan 15 150 0.5× 94 0.5× 176 1.1× 56 0.4× 72 0.7× 49 645
Jianqing Liang China 16 152 0.5× 160 0.9× 81 0.5× 47 0.4× 57 0.5× 40 626
Wen Gao China 13 79 0.3× 193 1.1× 127 0.8× 70 0.5× 95 0.9× 51 760
Ming Wan China 12 69 0.2× 235 1.3× 83 0.5× 194 1.5× 156 1.5× 56 584
Robert Underwood United States 12 52 0.2× 316 1.7× 205 1.3× 111 0.8× 177 1.7× 53 1.1k
Marek Śmieja Poland 11 65 0.2× 140 0.8× 106 0.7× 332 2.5× 144 1.4× 37 839

Countries citing papers authored by Weihao Kong

Since Specialization
Citations

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

Fields of papers citing papers by Weihao Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weihao Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Weihao Kong. A scholar is included among the top collaborators of Weihao Kong 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 Weihao Kong. Weihao Kong 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.
Wu, Zhenyu, et al.. (2025). The Roles of Forkhead Box O3a (FOXO3a) in Bone and Cartilage Diseases – A Narrative Review. Drug Design Development and Therapy. Volume 19. 1357–1375. 5 indexed citations
2.
Kong, Weihao, et al.. (2025). Proteomic and Amino Acid Dynamics During Jujube Blackening: Structural Transformations and Maillard Reaction Linkages. Food Science & Nutrition. 13(7). e70644–e70644.
3.
Kong, Weihao, Qi Guo, Yongwei Zhao, et al.. (2024). Cambricon-D: Full-Network Differential Acceleration for Diffusion Models. 903–914. 5 indexed citations
4.
Wang, Zeyu, Weimei Shi, Longhuo Wu, et al.. (2024). TMF inhibits extracellular matrix degradation by regulating the C/EBPβ/ADAMTS5 signaling pathway in osteoarthritis. Biomedicine & Pharmacotherapy. 174. 116501–116501. 4 indexed citations
5.
Liu, Zhaowen, et al.. (2023). C/EBPβ: The structure, regulation, and its roles in inflammation-related diseases. Biomedicine & Pharmacotherapy. 169. 115938–115938. 28 indexed citations
6.
Chen, Zhixi, et al.. (2023). Geniposide stimulates autophagy by activating the GLP-1R/AMPK/mTOR signaling in osteoarthritis chondrocytes. Biomedicine & Pharmacotherapy. 167. 115595–115595. 13 indexed citations
7.
Zhou, Liming, et al.. (2022). Cleavage Stimulation Factor Subunit 2: Function Across Cancers and Potential Target for Chemotherapeutic Drugs. Frontiers in Pharmacology. 13. 852469–852469. 1 indexed citations
8.
Zhang, Zhenyu, Jianlin Zhang, Chong Li, et al.. (2022). An m6A-Related lncRNA Signature Predicts the Prognosis of Hepatocellular Carcinoma. Frontiers in Pharmacology. 13. 854851–854851. 10 indexed citations
9.
Zhang, Jianlin, Min Zhang, Jin Huang, et al.. (2021). Development and Validation of an Autophagy‐Related Gene Signature for Predicting the Prognosis of Hepatocellular Carcinoma. BioMed Research International. 2021(1). 7771037–7771037. 11 indexed citations
10.
Kong, Weihao, et al.. (2021). A combined prediction method for reducing prediction uncertainty in the quantitative mineral resources prediction. Dixue qianyuan. 28(3). 128. 2 indexed citations
11.
Liu, Rongqiang, et al.. (2021). A Novel Nine-Gene Signature Associated With Immune Infiltration for Predicting Prognosis in Hepatocellular Carcinoma. Frontiers in Genetics. 12. 730732–730732. 3 indexed citations
12.
Li, Liang‐yun, Junfa Yang, Shuang Hu, et al.. (2021). ZEB1 serves an oncogenic role in the tumourigenesis of HCC by promoting cell proliferation, migration, and inhibiting apoptosis via Wnt/β-catenin signaling pathway. Acta Pharmacologica Sinica. 42(10). 1676–1689. 28 indexed citations
13.
Kong, Weihao, Mingwei Yang, Jianfeng Zhang, et al.. (2021). Prognostic value of inflammation-based indices in patients with resected hepatocellular carcinoma. BMC Cancer. 21(1). 469–469. 6 indexed citations
14.
Kong, Weihao, et al.. (2020). Development and Validation of an Immune-Related lncRNA Signature for Predicting the Prognosis of Hepatocellular Carcinoma. Frontiers in Genetics. 11. 1037–1037. 23 indexed citations
15.
Wu, Xiao‐Tao, et al.. (2019). Improved perioperative quality of life in endoscopic sinus surgery by application of enhanced recovery after surgery. SHILAP Revista de lepidopterología.
16.
Liang, Hao, Zhiyong Xiong, Zhicheng Yao, et al.. (2018). Inhibiting effect and its mechanism of BDH2 gene on the proliferation of liver cancer cells. 7(4). 327–331. 1 indexed citations
17.
Kong, Weihao, et al.. (2018). Prognostic value of miR-17-5p in cancers: a meta-analysis. OncoTargets and Therapy. Volume 11. 3541–3549. 10 indexed citations
18.
Kong, Weihao, et al.. (2017). Learning Populations of Parameters. Neural Information Processing Systems. 30. 5778–5787. 2 indexed citations
19.
Kong, Weihao, Jian Li, Tao Qin, & Tie‐Yan Liu. (2013). Optimal Allocation for Chunked-Reward Advertising. arXiv (Cornell University). 3 indexed citations
20.
Kong, Weihao & Wu-Jun Li. (2012). Isotropic Hashing. Neural Information Processing Systems. 25. 1646–1654. 189 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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