Kaiting Wang

1.4k total citations · 1 hit paper
17 papers, 565 citations indexed

About

Kaiting Wang is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Kaiting Wang has authored 17 papers receiving a total of 565 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Oncology. Recurrent topics in Kaiting Wang's work include Cancer Mechanisms and Therapy (2 papers), Pancreatic and Hepatic Oncology Research (2 papers) and RNA modifications and cancer (2 papers). Kaiting Wang is often cited by papers focused on Cancer Mechanisms and Therapy (2 papers), Pancreatic and Hepatic Oncology Research (2 papers) and RNA modifications and cancer (2 papers). Kaiting Wang collaborates with scholars based in China, Taiwan and Hong Kong. Kaiting Wang's co-authors include Lei Chen, Yan Zhao, Yani Zhang, Hongyang Wang, Siyun Shen, Xinyao Qiu, Rui Wu, Xuan Wu, Shan Wang and Yanjing Zhu and has published in prestigious journals such as Cancer Research, Nanoscale and Physical Chemistry Chemical Physics.

In The Last Decade

Kaiting Wang

17 papers receiving 559 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

M6A Demethylase ALKBH5 Regulates PD-L1 Expression and Tumor Immunoenvironment in Intrahepatic Cholangiocarcinoma

2021 174 citations Xinyao Qiu, Shuai Yang et al. Cancer Research profile →

Peers

Kaiting Wang

ONCOL

HEPAT

PRM

Zhongwei Zhao China

Bai Ji China

Haotian Liao China

Jizhou Tan China

Xuan Meng China

Shoujie Zhao China

Amane Takahashi Japan

Xiong Lei China

Mi Jang South Korea

Mengdi Liang China

Zhongwei Zhao China

Kaiting Wang

178 ×0.6

140 ×0.7

71 ×0.4

ONCOL

72 ×0.6

HEPAT

98 ×1.3

PRM

Citations per year, relative to Kaiting Wang Kaiting Wang (= 1×) peers Zhongwei Zhao

Countries citing papers authored by Kaiting Wang

Since Specialization

Citations

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

Fields of papers citing papers by Kaiting Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaiting Wang

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

All Works

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17 of 17 papers shown

Zhang, Ruixin, et al.. (2025). Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX. Breast Cancer Research. 27(1). 178–178. 1 indexed citations

Wang, Kaiting, Zihan Zhao, Shensi Shen, et al.. (2025). ALKBH5 deficiency suppresses hepatocarcinogenesis in mice via m6A-dependent STAT1 restoration. Acta Pharmacologica Sinica. 47(1). 209–221. 1 indexed citations

Wang, Kaiting, Iftikhar Hussain, Karanpal Singh, & Kaili Zhang. (2025). Fabrication of MXene films through various techniques: a mini review. Nanoscale. 17(26). 15676–15689. 2 indexed citations

Wang, Kaiting, et al.. (2024). DanceOnStage: positioning training of dancing stage performance in virtual reality. 270–274. 1 indexed citations

Wang, Kaiting, Jianmin Wu, Yang Zhao, et al.. (2024). Hyperactivation of β-catenin signal in hepatocellular carcinoma recruits myeloid-derived suppressor cells through PF4-CXCR3 axis. Cancer Letters. 586. 216690–216690. 11 indexed citations

Qiu, Xinyao, Tao Zhou, Shuai Li, et al.. (2024). Spatial single-cell protein landscape reveals vimentinhigh macrophages as immune-suppressive in the microenvironment of hepatocellular carcinoma. Nature Cancer. 5(10). 1557–1578. 23 indexed citations

Wang, Kaiting, et al.. (2024). Evolutionary analysis of CBFs/DREB1s in temperate and tropical woody bamboos and functional study of PeDREB1A3 under cold and drought stress. Plant Physiology and Biochemistry. 219. 109392–109392. 2 indexed citations

Lu, Hai‐Wen, et al.. (2024). Identification of SnRK2 family and functional study of PeSnRK2.2A and PeSnRK2.2B for drought resistance in Phyllostachys edulis. Industrial Crops and Products. 219. 119087–119087. 2 indexed citations

Qiu, Xinyao, Shuai Yang, Shan Wang, et al.. (2021). M6A Demethylase ALKBH5 Regulates PD-L1 Expression and Tumor Immunoenvironment in Intrahepatic Cholangiocarcinoma. Cancer Research. 81(18). 4778–4793. 174 indexed citations breakdown →

10.

Wang, Kaiting, Xinyao Qiu, Yan Zhao, Hongyang Wang, & Lei Chen. (2021). The Wnt/β-catenin signaling pathway in the tumor microenvironment of hepatocellular carcinoma. Cancer Biology and Medicine. 18(-). 0–0. 20 indexed citations

11.

Zhao, Yan, Zhixuan Li, Yanjing Zhu, et al.. (2021). Single‐Cell Transcriptome Analysis Uncovers Intratumoral Heterogeneity and Underlying Mechanisms for Drug Resistance in Hepatobiliary Tumor Organoids. Advanced Science. 8(11). e2003897–e2003897. 93 indexed citations

12.

Wu, Tong, Yingcheng Yang, Bo Zheng, et al.. (2021). Distinct Immune Signatures in Peripheral Blood Predict Chemosensitivity in Intrahepatic Cholangiocarcinoma Patients. Engineering. 7(10). 1381–1392. 3 indexed citations

13.

Wang, Kaiting, et al.. (2020). Efficacy and safety of micro-implant anchorage in Angle class II malocclusion orthodontic treatment. Medicine. 99(50). e23221–e23221. 6 indexed citations

14.

Zhao, Yan, Yani Zhang, Kaiting Wang, & Lei Chen. (2020). Lenvatinib for hepatocellular carcinoma: From preclinical mechanisms to anti-cancer therapy. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1874(1). 188391–188391. 180 indexed citations

15.

Wang, Kaiting, Santhanamoorthi Nachimuthu, & Jyh‐Chiang Jiang. (2018). Temperature-programmed desorption studies of NH₃ and H₂O on the RuO₂(110) surface: effects of adsorbate diffusion. Physical Chemistry Chemical Physics. 20(37). 24201–24209. 17 indexed citations

16.

Ma, Zhichao, Hongwei Zhao, Kaiting Wang, et al.. (2013). Novel correction methods on a miniature tensile device based on a modular non-standard layout. Measurement Science and Technology. 24(8). 85901–85901. 13 indexed citations

17.

Ma, Zhichao, et al.. (2013). Novel in situ device for investigating the tensile and fatigue behaviors of bulk materials. Review of Scientific Instruments. 84(4). 45104–45104. 16 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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