Peng Lee

7.4k total citations
149 papers, 5.9k citations indexed

About

Peng Lee is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Peng Lee has authored 149 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Molecular Biology, 56 papers in Pulmonary and Respiratory Medicine and 37 papers in Cancer Research. Recurrent topics in Peng Lee's work include Prostate Cancer Treatment and Research (47 papers), Estrogen and related hormone effects (16 papers) and Cancer-related molecular mechanisms research (14 papers). Peng Lee is often cited by papers focused on Prostate Cancer Treatment and Research (47 papers), Estrogen and related hormone effects (16 papers) and Cancer-related molecular mechanisms research (14 papers). Peng Lee collaborates with scholars based in United States, China and United Kingdom. Peng Lee's co-authors include Jonathan Melamed, Garrett Daniels, Jian‐Jun Wei, Xinyu Wu, Marie E. Monaco, Eva Hernando, Jian-Jun Wei, Iman Osman, Xuanyi Zou and Fang‐Ming Deng and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Peng Lee

145 papers receiving 5.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peng Lee United States 44 3.3k 2.0k 1.5k 1.1k 541 149 5.9k
Robbert J.C. Slebos United States 40 4.1k 1.2× 1.8k 0.9× 1.2k 0.8× 2.2k 2.1× 418 0.8× 97 7.7k
Paul Van Hummelen Belgium 44 2.7k 0.8× 1.5k 0.8× 617 0.4× 803 0.7× 800 1.5× 125 6.2k
Kwong‐Kwok Wong United States 48 4.0k 1.2× 1.7k 0.8× 634 0.4× 1.4k 1.3× 531 1.0× 131 6.7k
Yohei Miyagi Japan 47 3.4k 1.0× 1.8k 0.9× 1.6k 1.1× 2.3k 2.1× 473 0.9× 324 8.2k
Nam Hoon Cho South Korea 38 1.8k 0.5× 991 0.5× 1.2k 0.8× 1.3k 1.2× 233 0.4× 223 4.9k
Jin Bai China 44 3.0k 0.9× 1.3k 0.7× 670 0.5× 922 0.8× 150 0.3× 233 6.4k
Qianxing Mo United States 39 3.2k 1.0× 1.0k 0.5× 933 0.6× 1.8k 1.7× 545 1.0× 138 6.2k
Izhak Haviv Australia 29 2.3k 0.7× 1.2k 0.6× 480 0.3× 1.3k 1.2× 356 0.7× 56 4.4k
Liang Hu China 39 2.8k 0.8× 1.1k 0.6× 350 0.2× 1.5k 1.4× 607 1.1× 201 5.8k
Anthony M. Magliocco Canada 38 1.3k 0.4× 853 0.4× 1.1k 0.7× 1.8k 1.6× 279 0.5× 136 4.2k

Countries citing papers authored by Peng Lee

Since Specialization
Citations

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

Fields of papers citing papers by Peng Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Peng Lee. A scholar is included among the top collaborators of Peng Lee 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 Peng Lee. Peng Lee 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, Fa, Qing Zhu, Kunxiaojia Yuan, et al.. (2024). Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method. Earth s Future. 12(10). 3 indexed citations
2.
3.
4.
Deng, Fang‐Ming, et al.. (2017). Chromatin-Associated Protein SIN3B Prevents Prostate Cancer Progression by Inducing Senescence. Cancer Research. 77(19). 5339–5348. 9 indexed citations
5.
Yang, Zhan, Guanyi Zhang, Xiaojie Wang, et al.. (2016). Interplay between Cytoplasmic and Nuclear Androgen Receptor Splice Variants Mediates Castration Resistance. Molecular Cancer Research. 15(1). 59–68. 55 indexed citations
6.
Liang, Jiaqian, Yirong Li, Garrett Daniels, et al.. (2015). LEF1 Targeting EMT in Prostate Cancer Invasion Is Regulated by miR-34a. Molecular Cancer Research. 13(4). 681–688. 78 indexed citations
7.
Wu, Xinyu, Garrett Daniels, Peng Lee, & Marie E. Monaco. (2014). Lipid metabolism in prostate cancer.. PubMed Central. 159 indexed citations
8.
Liu, Zhaojian, Xiyu Zhang, Xiaofei Xu, et al.. (2013). miR-106a Represses the Rb Tumor Suppressor p130 to Regulate Cellular Proliferation and Differentiation in High-Grade Serous Ovarian Carcinoma. Molecular Cancer Research. 11(11). 1314–1325. 41 indexed citations
9.
Daniels, Garrett, Yi‐Rong Li, Lan L. Gellert, et al.. (2013). TBLR1 as an androgen receptor (AR) coactivator selectively activates AR target genes to inhibit prostate cancer growth. Endocrine Related Cancer. 21(1). 127–142. 33 indexed citations
10.
Wu, Xinyu, Shiaoching Gong, Pradip Roy‐Burman, Peng Lee, & Zoran Čulig. (2013). Current mouse and cell models in prostate cancer research. Endocrine Related Cancer. 20(4). R155–R170. 93 indexed citations
11.
Ren, Qinghu, Liying Zhang, Rachel Ruoff, et al.. (2013). Expression of androgen receptor and its phosphorylated forms in breast cancer progression. Cancer. 119(14). 2532–2540. 21 indexed citations
12.
Li, Yirong, Martin Ligr, James P. McCarron, et al.. (2011). Natura-Alpha Targets Forkhead Box M1 and Inhibits Androgen-Dependent and -Independent Prostate Cancer Growth and Invasion. Clinical Cancer Research. 17(13). 4414–4424. 31 indexed citations
13.
Liu, Zhaojian, Changshun Shao, Yaoqin Gong, et al.. (2011). HMGA2 Overexpression-Induced Ovarian Surface Epithelial Transformation Is Mediated Through Regulation of EMT Genes. Cancer Research. 71(2). 349–359. 130 indexed citations
14.
Wang, Daguang, Fei Ye, Yabin Sun, et al.. (2011). Protein Signatures for Classification and Prognosis of Gastric Cancer. American Journal Of Pathology. 179(4). 1657–1666. 25 indexed citations
15.
Hatcher, David, Paul J. Christos, Amy Rose, et al.. (2011). Impact of race on survival in patients with clinically nonmetastatic prostate cancer who deferred primary treatment. Cancer. 118(12). 3145–3152. 14 indexed citations
16.
Ligr, Martin, Ruzeen Patwa, Garrett Daniels, et al.. (2011). Correction: Expression and Function of Androgen Receptor Coactivator p44/Mep50/WDR77 in Ovarian Cancer. PLoS ONE. 6(10). 11 indexed citations
17.
Wei, Jian‐Jun, Xinyu Wu, Yi Peng, et al.. (2010). Regulation of HMGA1 Expression by MicroRNA-296 Affects Prostate Cancer Growth and Invasion. Clinical Cancer Research. 17(6). 1297–1305. 67 indexed citations
18.
Ligr, Martin, Yi‐Rong Li, Xuanyi Zou, et al.. (2010). Tumor Suppressor Function of Androgen Receptor Coactivator ARA70α in Prostate Cancer. American Journal Of Pathology. 176(4). 1891–1900. 27 indexed citations
19.
Segura, Miguel F., Douglas Hanniford, Sílvia Menéndez, et al.. (2009). Aberrant miR-182 expression promotes melanoma metastasis by repressing FOXO3 and microphthalmia-associated transcription factor. Proceedings of the National Academy of Sciences. 106(6). 1814–1819. 451 indexed citations
20.
Xiao, Xiaoqiang, et al.. (2008). Inventory based speech denoising with hidden Markov models. European Signal Processing Conference. 1–5. 2 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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