Hee Won Yang

2.7k total citations
39 papers, 1.9k citations indexed

About

Hee Won Yang is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Hee Won Yang has authored 39 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 12 papers in Oncology and 12 papers in Cell Biology. Recurrent topics in Hee Won Yang's work include Microtubule and mitosis dynamics (10 papers), Cancer-related Molecular Pathways (9 papers) and Advanced Breast Cancer Therapies (8 papers). Hee Won Yang is often cited by papers focused on Microtubule and mitosis dynamics (10 papers), Cancer-related Molecular Pathways (9 papers) and Advanced Breast Cancer Therapies (8 papers). Hee Won Yang collaborates with scholars based in United States, South Korea and Germany. Hee Won Yang's co-authors include Tobias Meyer, Mingyu Chung, Won Do Heo, Sean R. Collins, Feng‐Chiao Tsai, Arnold Hayer, Takamasa Kudo, Kwang‐Hyun Cho, Sangkyu Lee and Akiko Seki and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Hee Won Yang

36 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hee Won Yang United States 23 1.0k 513 389 212 176 39 1.9k
Monica Giannotta Italy 18 823 0.8× 476 0.9× 178 0.5× 104 0.5× 116 0.7× 25 1.7k
Mariano S. Viapiano United States 31 996 1.0× 469 0.9× 299 0.8× 366 1.7× 153 0.9× 73 2.4k
Luo Lu United States 25 1.2k 1.1× 422 0.8× 241 0.6× 178 0.8× 210 1.2× 81 2.3k
Stavros Taraviras Greece 31 2.2k 2.1× 528 1.0× 498 1.3× 261 1.2× 139 0.8× 91 3.2k
Irina Arnaoutova United States 15 953 0.9× 441 0.9× 430 1.1× 136 0.6× 88 0.5× 23 2.1k
Yiming Zhou China 24 1.4k 1.3× 577 1.1× 425 1.1× 165 0.8× 197 1.1× 74 2.5k
Shoutian Zhu United States 21 1.4k 1.4× 325 0.6× 398 1.0× 95 0.4× 135 0.8× 33 2.7k
Melissa G. Mendez United States 13 1.9k 1.9× 1.1k 2.2× 361 0.9× 105 0.5× 124 0.7× 17 3.0k
Pavel Krejčı́ Czechia 34 2.2k 2.1× 385 0.8× 403 1.0× 95 0.4× 196 1.1× 94 3.0k
Sangmyung Rhee South Korea 26 873 0.8× 585 1.1× 253 0.7× 82 0.4× 95 0.5× 68 1.8k

Countries citing papers authored by Hee Won Yang

Since Specialization
Citations

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

Fields of papers citing papers by Hee Won Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hee Won Yang. 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 Hee Won Yang. The network helps show where Hee Won Yang may publish in the future.

Co-authorship network of co-authors of Hee Won Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Hee Won Yang. A scholar is included among the top collaborators of Hee Won Yang 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 Hee Won Yang. Hee Won Yang 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.
Kim, Sungsoo, et al.. (2025). Dual targeting of CDK4/6 and CDK7 augments tumor response and antitumor immunity in breast cancer models. Journal of Clinical Investigation. 135(20). 1 indexed citations
2.
Kim, Jae Hyun, et al.. (2025). E2F activity determines mitosis versus whole-genome duplication in G2-arrested cells. Nature Communications. 16(1). 6677–6677. 1 indexed citations
3.
4.
Yang, Hee Won, et al.. (2025). Targeting CDK4/6 in breast cancer. Experimental & Molecular Medicine. 57(2). 312–322. 9 indexed citations
5.
Yang, Hee Won. (2024). Investigating Heterogeneous Cell-Cycle Progression Using Single-Cell Imaging Approaches. Methods in molecular biology. 2740. 263–273. 4 indexed citations
6.
Kim, Sung Soo, Anton Safonov, Rajesh K. Soni, et al.. (2023). Sequential activation of E2F via Rb degradation and c-Myc drives resistance to CDK4/6 inhibitors in breast cancer. Cell Reports. 42(11). 113198–113198. 27 indexed citations
7.
Kim, Sungsoo, Subrata Chowdhury, Carrie J. Shawber, et al.. (2023). Angiopoietin-2–Dependent Spatial Vascular Destabilization Promotes T-cell Exclusion and Limits Immunotherapy in Melanoma. Cancer Research. 83(12). 1968–1983. 24 indexed citations
8.
Chowdhury, Subrata, Sungsoo Kim, Richard A. Friedman, et al.. (2023). Angiopoietin-2 blockade suppresses growth of liver metastases from pancreatic neuroendocrine tumors by promoting T cell recruitment. Journal of Clinical Investigation. 133(20). 8 indexed citations
9.
Kim, Sungsoo, et al.. (2023). Non-canonical pathway for Rb inactivation and external signaling coordinate cell-cycle entry without CDK4/6 activity. Nature Communications. 14(1). 7847–7847. 24 indexed citations
10.
Kim, Sung Soo, Richard D. Carvajal, Minah Kim, & Hee Won Yang. (2023). Kinetics of RTK activation determine ERK reactivation and resistance to dual BRAF/MEK inhibition in melanoma. Cell Reports. 42(6). 112570–112570. 20 indexed citations
11.
Nguyen, Trang, Enyuan Shang, Chang Shu, et al.. (2021). Aurora kinase A inhibition reverses the Warburg effect and elicits unique metabolic vulnerabilities in glioblastoma. Nature Communications. 12(1). 5203–5203. 76 indexed citations
12.
Liu, Chad, Mingyu Chung, Leighton H. Daigh, et al.. (2020). Altered G1 signaling order and commitment point in cells proliferating without CDK4/6 activity. Nature Communications. 11(1). 5305–5305. 33 indexed citations
13.
Tsai, Tony, Sean R. Collins, Caleb K. Chan, et al.. (2019). Efficient Front-Rear Coupling in Neutrophil Chemotaxis by Dynamic Myosin II Localization. Developmental Cell. 49(2). 189–205.e6. 50 indexed citations
14.
Chung, Mingyu, et al.. (2019). Transient Hysteresis in CDK4/6 Activity Underlies Passage of the Restriction Point in G1. Molecular Cell. 76(4). 562–573.e4. 66 indexed citations
15.
Yang, Hee Won, Mingyu Chung, Takamasa Kudo, & Tobias Meyer. (2017). Competing memories of mitogen and p53 signalling control cell-cycle entry. Nature. 549(7672). 404–408. 157 indexed citations
16.
Hayer, Arnold, Lin Shao, Mingyu Chung, et al.. (2016). Engulfed cadherin fingers are polarized junctional structures between collectively migrating endothelial cells. Nature Cell Biology. 18(12). 1311–1323. 193 indexed citations
17.
Yang, Hee Won, Sean R. Collins, & Tobias Meyer. (2015). Locally excitable Cdc42 signals steer cells during chemotaxis. Nature Cell Biology. 18(2). 191–201. 131 indexed citations
18.
Collins, Sean R., et al.. (2015). Using light to shape chemical gradients for parallel and automated analysis of chemotaxis. Molecular Systems Biology. 11(4). 804–804. 29 indexed citations
19.
Yang, Hee Won, Min‐Gyoung Shin, Sangkyu Lee, et al.. (2012). Cooperative Activation of PI3K by Ras and Rho Family Small GTPases. Molecular Cell. 47(2). 281–290. 140 indexed citations
20.
Won, Jae‐Kyung, Hee Won Yang, Sung‐Young Shin, et al.. (2012). The crossregulation between ERK and PI3K signaling pathways determines the tumoricidal efficacy of MEK inhibitor. Journal of Molecular Cell Biology. 4(3). 153–163. 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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