Sungwoo Ahn

538 total citations · 1 hit paper
17 papers, 361 citations indexed

About

Sungwoo Ahn is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Sungwoo Ahn has authored 17 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Oncology, 8 papers in Molecular Biology and 8 papers in Cancer Research. Recurrent topics in Sungwoo Ahn's work include Molecular Biology Techniques and Applications (5 papers), HER2/EGFR in Cancer Research (4 papers) and Cancer Genomics and Diagnostics (4 papers). Sungwoo Ahn is often cited by papers focused on Molecular Biology Techniques and Applications (5 papers), HER2/EGFR in Cancer Research (4 papers) and Cancer Genomics and Diagnostics (4 papers). Sungwoo Ahn collaborates with scholars based in South Korea, United States and Canada. Sungwoo Ahn's co-authors include Hyeyoung Lee, Sunyoung Park, Kwang Hwa Park, Sunghyun Kim, Geehyuk Kim, Dongsup Lee, Jungho Kim, Hyeeun Bang, Ranjan Maity and Marc‐Steffen Raab and has published in prestigious journals such as Blood, Cancer Cell and International Journal of Molecular Sciences.

In The Last Decade

Sungwoo Ahn

16 papers receiving 358 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.

The pre-existing T cell landscape determines the response to bispecific T cell engagers in multiple myeloma patients

2023 131 citations Mirco Friedrich, Paola Neri et al. Cancer Cell profile →

Peers

Sungwoo Ahn

ONCOL

RNMI

HEMAT

Xiaojie Xu China

Nan Huo China

Irene Manrique Spain

Guowen Lin China

Matthew R. Strickland United States

Zhihua Li China

Vivian Barry-Hamilton United States

Linda Hylander-Gans United States

Miso Kim South Korea

Xiaojie Xu China

Sungwoo Ahn

173 ×0.9

72 ×0.4

123 ×0.8

ONCOL

131 ×2.2

RNMI

34 ×0.6

HEMAT

Citations per year, relative to Sungwoo Ahn Sungwoo Ahn (= 1×) peers Xiaojie Xu

Countries citing papers authored by Sungwoo Ahn

Since Specialization

Citations

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

Fields of papers citing papers by Sungwoo Ahn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sungwoo Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Sungwoo Ahn. A scholar is included among the top collaborators of Sungwoo Ahn 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 Sungwoo Ahn. Sungwoo Ahn 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

Lee, Holly, Sungwoo Ahn, Mansour Poorebrahim, et al.. (2024). Tumor Intrinsic and Antigen-Independent Resistance Mechanisms to Bispecific T Cell Engagers in Multiple Myeloma. Blood. 144(Supplement 1). 1892–1892. 1 indexed citations

Lee, Holly, Mansour Poorebrahim, Sacha Benaoudia, et al.. (2024). BCMA Extracellular Domain Functional Hotspots and Resistance to Variable Anti-BCMA T Cell Engagers in Multiple Myeloma. Blood. 144(Supplement 1). 4651–4651. 1 indexed citations

Kim, Youngmin, et al.. (2024). Recompiling QAOA Circuits on Various Rotational Directions. 309–324. 1 indexed citations

Friedrich, Mirco, Paola Neri, Simon Steiger, et al.. (2023). The pre-existing T cell landscape determines the response to bispecific T cell engagers in multiple myeloma patients. Cancer Cell. 41(4). 711–725.e6. 131 indexed citations breakdown →

Park, Sun-Young, Sungwoo Ahn, Jee Ye Kim, et al.. (2022). Blood Test for Breast Cancer Screening through the Detection of Tumor-Associated Circulating Transcripts. International Journal of Molecular Sciences. 23(16). 9140–9140. 8 indexed citations

Park, Sunyoung, Jungho Kim, Sehee Oh, et al.. (2019). microRNA-944 overexpression is a biomarker for poor prognosis of advanced cervical cancer. BMC Cancer. 19(1). 419–419. 37 indexed citations

Park, Sangjung, Sunyoung Park, Jungho Kim, et al.. (2018). Assessment of Ki-67 for Predicting Effective Prognosis in Breast Cancer Subtypes. Journal of Experimental & Biomedical Sciences/Biomedical Science Letters. 24(1). 9–14. 3 indexed citations

Kim, Geehyuk, Jungho Kim, Sunyoung Park, et al.. (2018). Diagnostic Availability of Estrogen Receptor Alpha mRNA on Cervical Cancer Tissue. Korean Journal of Clinical Laboratory Science. 50(4). 449–456. 1 indexed citations

Ahn, Sungwoo, et al.. (2018). Characterization of CCND1 and TWIST1 as Prognostic Markers with the Mortality Rate of Breast Cancer. Journal of Experimental & Biomedical Sciences/Biomedical Science Letters. 24(2). 76–86. 1 indexed citations

10.

Park, Sunyoung, Jungho Kim, Hyeeun Bang, et al.. (2017). MiR-9, miR-21, and miR-155 as potential biomarkers for HPV positive and negative cervical cancer. BMC Cancer. 17(1). 658–658. 111 indexed citations

11.

Park, Sunyoung, Hyeonseok Yoon, Hyeeun Bang, et al.. (2017). Analytical Performance of Sensitivity and Specificity for Rapid Multiplex High Risk Human Papillomavirus Detection Kit: HPV ViroCheck. Korean Journal of Clinical Laboratory Science. 49(4). 446–454. 2 indexed citations

12.

Ahn, Sungwoo, et al.. (2016). Clinical Usefulness of a One-Tube Nested Reverse Transcription Quantitative Polymerase Chain Reaction Assay for Evaluating Human Epidermal Growth Factor Receptor 2 mRNA Overexpression in Formalin-Fixed and Paraffin-Embedded Breast Cancer Tissue Samples. Pathobiology. 84(2). 57–70. 2 indexed citations

13.

Ahn, Sungwoo, Sunghyun Kim, Sunyoung Park, et al.. (2015). Detection of circulating tumor cell-specific markers in breast cancer patients using the quantitative RT-PCR assay. International Journal of Clinical Oncology. 20(5). 878–890. 24 indexed citations

14.

Park, Sangjung, Sunghyun Kim, Sungwoo Ahn, et al.. (2014). Quantitative RT-PCR assay of HER2 mRNA expression in formalin-fixed and paraffin-embedded breast cancer tissues.. PubMed. 7(10). 6752–9. 14 indexed citations

15.

Ahn, Sungwoo, Sunghyun Kim, Sunyoung Park, et al.. (2014). Detection of circulating tumor cells in patients with breast cancer using the quantitative RT-PCR assay for monitoring of therapy efficacy. Experimental and Molecular Pathology. 97(3). 445–452. 14 indexed citations

16.

Park, Sangjung, Sunghyun Kim, Sungwoo Ahn, et al.. (2014). Quantitative RT-PCR assay of HER2 mRNA expression in formalin-fixed and paraffin-embedded breast cancer tissues. PubMed Central. 7(10). 6752–6759. 10 indexed citations

17.

Park, Sangjung, Sunghyun Kim, Sungwoo Ahn, et al.. (2014). Evaluation of BrightGen HR RT-qDx assay to detect nuclear receptors mRNA overexpression in FFPE breast cancer tissue samples for selection of tamoxifen therapy.. PubMed Central. 7(9). 5792–5800.

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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