Yao Dai

1.6k total citations
49 papers, 1.3k citations indexed

About

Yao Dai is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Yao Dai has authored 49 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 14 papers in Cancer Research and 12 papers in Oncology. Recurrent topics in Yao Dai's work include Cell death mechanisms and regulation (8 papers), Cancer, Hypoxia, and Metabolism (7 papers) and PI3K/AKT/mTOR signaling in cancer (5 papers). Yao Dai is often cited by papers focused on Cell death mechanisms and regulation (8 papers), Cancer, Hypoxia, and Metabolism (7 papers) and PI3K/AKT/mTOR signaling in cancer (5 papers). Yao Dai collaborates with scholars based in United States, China and Japan. Yao Dai's co-authors include Dietmar W. Siemann, Theodore S. Lawrence, Liang Xu, Wenhua Tang, Kyung‐Mi Bae, Yang Meng, Jeffrey DeSano, Johannes Vieweg, Meilan Liu and Ezra Burstein and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Yao Dai

47 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yao Dai United States 20 758 300 268 153 136 49 1.3k
Cong Xu China 23 722 1.0× 303 1.0× 312 1.2× 234 1.5× 171 1.3× 78 1.6k
Xiaofang Zhang China 17 776 1.0× 161 0.5× 298 1.1× 99 0.6× 191 1.4× 68 1.4k
Wenying Yu China 25 816 1.1× 482 1.6× 181 0.7× 96 0.6× 187 1.4× 80 2.0k
Yongbo Liu China 23 1.1k 1.5× 226 0.8× 238 0.9× 56 0.4× 61 0.4× 74 1.7k
Rong Shen China 23 586 0.8× 215 0.7× 204 0.8× 114 0.7× 92 0.7× 91 1.5k
Hanlin Wang China 20 691 0.9× 228 0.8× 265 1.0× 104 0.7× 151 1.1× 90 1.3k
Jiemin Wang China 22 907 1.2× 162 0.5× 386 1.4× 81 0.5× 36 0.3× 66 1.5k
Sensen Lin China 22 643 0.8× 239 0.8× 241 0.9× 78 0.5× 29 0.2× 44 1.3k
Liang Chu China 27 1.5k 2.0× 385 1.3× 638 2.4× 112 0.7× 74 0.5× 65 2.2k

Countries citing papers authored by Yao Dai

Since Specialization
Citations

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

Fields of papers citing papers by Yao Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yao Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Yao Dai. A scholar is included among the top collaborators of Yao Dai 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 Yao Dai. Yao Dai 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.
Li, Jinliang, Yao Dai, Qian Chen, et al.. (2025). Inorganic-metal hybrid coating for stabilizing and regulating aqueous zinc anodes. Journal of Colloid and Interface Science. 687. 479–488. 7 indexed citations
2.
Liu, Xiaowen, Linjie Zhao, Yang Shen, et al.. (2025). Hierarchical Carbon‐Based Electrocatalyst with Functional Separation Properties for Efficient pH Universal Nitrate Reduction. Advanced Materials. 37(11). e2417623–e2417623. 19 indexed citations
3.
Dai, Yao, et al.. (2024). Collaborative optimization of distribution network and 5G base stations considering its communication load migration and energy storage dynamic backup flexibility. International Journal of Electrical Power & Energy Systems. 160. 110124–110124. 3 indexed citations
4.
Wang, Jinzeng, Xiaoyang Li, Ping Liu, et al.. (2024). A phase 2 pilot study of umbilical cord blood infusion as an adjuvant consolidation therapy in elderly patients with acute myeloid leukemia. Signal Transduction and Targeted Therapy. 9(1). 358–358. 1 indexed citations
5.
6.
Huang, Miao, Mai Tanaka, Peike Sheng, et al.. (2023). Functional Interrogation of Ca2+ Signals in Human Cancer Cells In Vitro and Ex Vivo by Fluorescent Microscopy and Molecular Tools. Methods in molecular biology. 2679. 95–125. 2 indexed citations
7.
Wu, Tao, Yao Dai, Yue Xu, et al.. (2023). ExosomePurity: tumour purity deconvolution in serum exosomes based on miRNA signatures. Briefings in Bioinformatics. 24(3). 1 indexed citations
8.
Huang, Yujie, et al.. (2022). Targeting mTOR Complex 2 in Castration-Resistant Prostate Cancer with Acquired Docetaxel Resistance. Drug Design Development and Therapy. Volume 16. 3817–3828. 1 indexed citations
9.
10.
Liu, Chuang, Junfei Zhao, Weiqiang Lü, et al.. (2020). Individualized genetic network analysis reveals new therapeutic vulnerabilities in 6,700 cancer genomes. PLoS Computational Biology. 16(2). e1007701–e1007701. 38 indexed citations
11.
Wang, Haiyun, Qi Lv, Yue Xu, et al.. (2019). An integrative pharmacogenomics analysis identifies therapeutic targets in KRAS-mutant lung cancer. EBioMedicine. 49. 106–117. 21 indexed citations
12.
Dai, Yao & Dietmar W. Siemann. (2019). <p>c-Src is required for hypoxia-induced metastasis-associated functions in prostate cancer cells</p>. OncoTargets and Therapy. Volume 12. 3519–3529. 17 indexed citations
13.
Zhan, Fei, Jingling Shen, Ruitao Wang, et al.. (2018). Role of exosomal small RNA in prostate cancer metastasis. Cancer Management and Research. Volume 10. 4029–4038. 12 indexed citations
14.
Dai, Yao & Dietmar W. Siemann. (2012). Constitutively active c-Met kinase in PC-3 cells is autocrine-independent and can be blocked by the Met kinase inhibitor BMS-777607. BMC Cancer. 12(1). 198–198. 20 indexed citations
15.
Dai, Yao, Kyung‐Mi Bae, Christine Pampo, & Dietmar W. Siemann. (2012). Impact of the small molecule Met inhibitor BMS-777607 on the metastatic process in a rodent tumor model with constitutive c-Met activation. Clinical & Experimental Metastasis. 29(3). 253–261. 23 indexed citations
16.
Dai, Yao, Kyung‐Mi Bae, & Dietmar W. Siemann. (2011). Another road leads to HIF-1 activation: implications for prostate cancer progression. Asian Journal of Andrology. 14(2). 241–242. 3 indexed citations
17.
Dai, Yao, Jeffrey DeSano, Yang Meng, et al.. (2009). Celastrol Potentiates Radiotherapy by Impairment of DNA Damage Processing in Human Prostate Cancer. International Journal of Radiation Oncology*Biology*Physics. 74(4). 1217–1225. 66 indexed citations
18.
Meng, Yang, Wenhua Tang, Yao Dai, et al.. (2008). Natural BH3 mimetic (-)-gossypol chemosensitizes human prostate cancer via Bcl-xL inhibition accompanied by increase of Puma and Noxa. Molecular Cancer Therapeutics. 7(7). 2192–2202. 167 indexed citations
19.
Dai, Yao, Wenhua Tang, Jeffrey DeSano, et al.. (2008). Molecularly Targeted Radiosensitization of Human Prostate Cancer by Modulating Inhibitor of Apoptosis. Clinical Cancer Research. 14(23). 7701–7710. 50 indexed citations
20.
Xu, Liang, Yao Dai, Yang Meng, et al.. (2007). Molecular radiosensitization of prostate cancer by modulating cell death pathways. Molecular Cancer Therapeutics. 6. 1 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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