Tae Hyun Hwang

3.3k total citations
49 papers, 992 citations indexed

About

Tae Hyun Hwang is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Tae Hyun Hwang has authored 49 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 16 papers in Molecular Biology and 11 papers in Cancer Research. Recurrent topics in Tae Hyun Hwang's work include Radiomics and Machine Learning in Medical Imaging (8 papers), Cancer Immunotherapy and Biomarkers (8 papers) and Cancer Genomics and Diagnostics (7 papers). Tae Hyun Hwang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (8 papers), Cancer Immunotherapy and Biomarkers (8 papers) and Cancer Genomics and Diagnostics (7 papers). Tae Hyun Hwang collaborates with scholars based in United States, South Korea and China. Tae Hyun Hwang's co-authors include Hongming Xu, Changjin Hong, Jean R. Clemenceau, Yunku Yeu, Sunho Park, Sung Hak Lee, Sunho Park, Xiaofeng Wu, Lawrence Lum and James Kim and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Tae Hyun Hwang

46 papers receiving 975 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tae Hyun Hwang United States 17 503 300 132 129 116 49 992
Lassi Paavolainen Finland 16 503 1.0× 174 0.6× 171 1.3× 97 0.8× 99 0.9× 36 1.0k
Fredrik Erlandsson Sweden 18 759 1.5× 255 0.8× 96 0.7× 103 0.8× 219 1.9× 36 1.5k
Yingtao Bi United States 20 626 1.2× 211 0.7× 203 1.5× 87 0.7× 158 1.4× 41 1.3k
Jennifer Bordeaux United States 16 605 1.2× 409 1.4× 192 1.5× 125 1.0× 139 1.2× 26 1.1k
Ting Zhuang China 20 800 1.6× 365 1.2× 237 1.8× 124 1.0× 115 1.0× 53 1.2k
Irena Radovanovic Canada 14 391 0.8× 211 0.7× 112 0.8× 111 0.9× 350 3.0× 16 1.1k
Anthony E. Rizzardi United States 11 295 0.6× 150 0.5× 106 0.8× 163 1.3× 74 0.6× 14 717
Robert Cornelison United States 18 770 1.5× 297 1.0× 230 1.7× 115 0.9× 114 1.0× 29 1.1k
Yunlong He China 19 657 1.3× 244 0.8× 222 1.7× 95 0.7× 69 0.6× 50 1.1k

Countries citing papers authored by Tae Hyun Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Tae Hyun Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tae Hyun Hwang. 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 Tae Hyun Hwang. The network helps show where Tae Hyun Hwang may publish in the future.

Co-authorship network of co-authors of Tae Hyun Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Tae Hyun Hwang. A scholar is included among the top collaborators of Tae Hyun Hwang 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 Tae Hyun Hwang. Tae Hyun Hwang 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.
Hamaidi, Imène, Alak Manna, İsmail Can, et al.. (2026). SIRT2-mediated deacetylation of LCK governs the magnitude of T cell receptor signaling. Nature Immunology. 27(2). 213–224.
2.
Shin, Su‐Jin, Geon Kim, Hyungjoo Cho, et al.. (2025). Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining. Nature Communications. 16(1). 4781–4781. 5 indexed citations
3.
Wang, Linghua, Mingyao Li, & Tae Hyun Hwang. (2024). The 3D Revolution in Cancer Discovery. Cancer Discovery. 14(4). 625–629. 10 indexed citations
4.
Kim, Geon, Hervé Hugonnet, Kyoohyun Kim, et al.. (2024). Holotomography. Nature Reviews Methods Primers. 4(1). 24 indexed citations
5.
Hong, Changjin, John D. Karalis, Suntrea T.G. Hammer, et al.. (2023). Gene expression profiles in Hispanic patients with early-onset gastric cancer.. Journal of Clinical Oncology. 41(4_suppl). 464–464. 1 indexed citations
6.
Hong, Changjin, Yoon Ho Choi, David N. Wald, & Tae Hyun Hwang. (2023). 1199 Identifying a source of dysfunctional CAR T cells incorporating with PBMC scRNA-seq data in patients with Non-Hodgkin Lymphoma. SHILAP Revista de lepidopterología. A1322–A1322. 2 indexed citations
7.
Hong, Changjin, Boro Dropulić, Paolo F. Caimi, et al.. (2022). Sequential Single-Cell Transcriptional and Protein Marker Profiling Reveals TIGIT as a Marker of CD19 CAR-T Cell Dysfunction in Patients with Non-Hodgkin Lymphoma. Cancer Discovery. 12(8). 1886–1903. 52 indexed citations
8.
Karalis, John D., Changjin Hong, Jean R. Clemenceau, et al.. (2022). ACTA2 Expression Predicts Survival and Is Associated with Response to Immune Checkpoint Inhibitors in Gastric Cancer. Clinical Cancer Research. 29(6). 1077–1085. 21 indexed citations
9.
Karalis, John D., Suntrea T.G. Hammer, Changjin Hong, et al.. (2022). Lenvatinib inhibits the growth of gastric cancer patient-derived xenografts generated from a heterogeneous population. Journal of Translational Medicine. 20(1). 116–116. 8 indexed citations
10.
11.
Kang, Jeonghyun, Jae‐Hoon Lee, Hye Sun Lee, et al.. (2021). Radiomics Features of 18F-Fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer. Cancers. 13(3). 392–392. 14 indexed citations
12.
Hong, Changjin, Boro Dropulić, Paolo F. Caimi, et al.. (2021). Sequential Single Cell Transcriptional and Protein Marker Profiling Reveals Tigit As a Marker of CD19 CAR-T Cell Dysfunction in Patients with Non-Hodgkin's Lymphoma. Blood. 138(Supplement 1). 164–164. 3 indexed citations
13.
Xu, Hongming, Fengyu Cong, & Tae Hyun Hwang. (2021). Machine Learning and Artificial Intelligence–driven Spatial Analysis of the Tumor Immune Microenvironment in Pathology Slides. European Urology Focus. 7(4). 706–709. 16 indexed citations
14.
Wang, Sam C., Yunku Yeu, Suntrea T.G. Hammer, et al.. (2020). Hispanic/Latino Patients with Gastric Adenocarcinoma Have Distinct Molecular Profiles Including a High Rate of Germline CDH1 Variants. Cancer Research. 80(11). 2114–2124. 21 indexed citations
15.
Tuladhar, Rubina, Yunku Yeu, John T. Piazza, et al.. (2019). CRISPR-Cas9-based mutagenesis frequently provokes on-target mRNA misregulation. Nature Communications. 10(1). 147 indexed citations
16.
Kim, Ann S., Matthew F. Kalady, Jennifer DeVecchio, et al.. (2019). Identifying miRNA Biomarkers and Predicted Targets Associated with Venous Thromboembolism in Colorectal Cancer Patients. Blood. 134(Supplement_1). 3643–3643. 8 indexed citations
17.
Aguilera, Kristina Y., Huocong Huang, Wenting Du, et al.. (2017). Inhibition of Discoidin Domain Receptor 1 Reduces Collagen-mediated Tumorigenicity in Pancreatic Ductal Adenocarcinoma. Molecular Cancer Therapeutics. 16(11). 2473–2485. 88 indexed citations
18.
Zhou, Xiaorong, Barrett L. Updegraff, Yabin Guo, et al.. (2016). PROTOCADHERIN 7 Acts through SET and PP2A to Potentiate MAPK Signaling by EGFR and KRAS during Lung Tumorigenesis. Cancer Research. 77(1). 187–197. 56 indexed citations
19.
Guo, Yabin, et al.. (2015). Comprehensive Ex Vivo Transposon Mutagenesis Identifies Genes That Promote Growth Factor Independence and Leukemogenesis. Cancer Research. 76(4). 773–786. 22 indexed citations
20.
Park, Sunho, Seung-Jun Kim, Donghyeon Yu, et al.. (2015). An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types. Bioinformatics. 32(11). 1643–1651. 19 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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