Soyoung Oh

3.1k total citations · 2 hit papers
20 papers, 2.2k citations indexed

About

Soyoung Oh is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Soyoung Oh has authored 20 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Immunology, 8 papers in Oncology and 5 papers in Molecular Biology. Recurrent topics in Soyoung Oh's work include T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (12 papers) and Immunotherapy and Immune Responses (8 papers). Soyoung Oh is often cited by papers focused on T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (12 papers) and Immunotherapy and Immune Responses (8 papers). Soyoung Oh collaborates with scholars based in United States, Singapore and Germany. Soyoung Oh's co-authors include Ming O. Li, Shomyseh Sanjabi, Huizhong Xiong, Andrew J. Caton, Sascha Rutz, Ahmed Toure, Michael L. Dustin, Jochen Huehn, Angelina M. Bilate and Yi Yang and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and The Journal of Experimental Medicine.

In The Last Decade

Soyoung Oh

18 papers receiving 2.2k citations

Hit Papers

Regulation of the Immune Response by TGF-β: From Concepti... 2017 2026 2020 2023 2017 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Soyoung Oh United States 17 1.5k 759 574 179 159 20 2.2k
Deepali Malhotra United States 20 1.8k 1.2× 627 0.8× 591 1.0× 183 1.0× 161 1.0× 43 2.5k
David Anz Germany 26 1.5k 1.0× 651 0.9× 758 1.3× 195 1.1× 104 0.7× 54 2.3k
Ignazia Prigione Italy 30 1.6k 1.1× 768 1.0× 615 1.1× 116 0.6× 184 1.2× 75 2.5k
Veronika Lukacs‐Kornek Germany 21 1.8k 1.2× 748 1.0× 522 0.9× 293 1.6× 105 0.7× 37 2.6k
Juan Dubrot Spain 25 1.4k 0.9× 841 1.1× 525 0.9× 276 1.5× 153 1.0× 45 2.1k
Frédérick Masson Australia 23 2.0k 1.3× 762 1.0× 610 1.1× 208 1.2× 92 0.6× 39 2.7k
Tomoya Katakai Japan 28 2.1k 1.4× 571 0.8× 881 1.5× 236 1.3× 237 1.5× 63 3.1k
Ivana M. Djuretic United States 16 1.7k 1.1× 573 0.8× 500 0.9× 112 0.6× 154 1.0× 27 2.3k
Alexander D. Barrow United States 25 2.0k 1.3× 556 0.7× 645 1.1× 127 0.7× 87 0.5× 38 2.8k
Andrea L. Szymczak-Workman United States 18 1.3k 0.9× 713 0.9× 465 0.8× 98 0.5× 176 1.1× 26 1.9k

Countries citing papers authored by Soyoung Oh

Since Specialization
Citations

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

Fields of papers citing papers by Soyoung Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soyoung Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Soyoung Oh. A scholar is included among the top collaborators of Soyoung Oh 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 Soyoung Oh. Soyoung Oh 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.
Oh, Soyoung, Kate Senger, Shravan Madireddi, et al.. (2022). High-efficiency nonviral CRISPR/Cas9-mediated gene editing of human T cells using plasmid donor DNA. The Journal of Experimental Medicine. 219(5). 50 indexed citations
2.
Senger, Kate, Ilseyar Akhmetzyanova, Benjamin Haley, Sascha Rutz, & Soyoung Oh. (2022). Plasmid‐Based Donor Templates for Nonviral CRISPR/Cas9‐Mediated Gene Knock‐In in Human T Cells. Current Protocols. 2(9). e538–e538.
3.
Oh, Soyoung, Dai-Chen Wu, Jeanne Cheung, et al.. (2020). PD-L1 expression by dendritic cells is a key regulator of T-cell immunity in cancer. Nature Cancer. 1(7). 681–691. 316 indexed citations breakdown →
4.
Oh, Soyoung, Akiko Seki, & Sascha Rutz. (2018). Ribonucleoprotein Transfection for CRISPR/Cas9‐Mediated Gene Knockout in Primary T Cells. Current Protocols in Immunology. 124(1). e69–e69. 30 indexed citations
5.
Hernandez, Sairy, Qing Jing, Xiangnan Du, et al.. (2018). The Kinase Activity of Hematopoietic Progenitor Kinase 1 Is Essential for the Regulation of T Cell Function. Cell Reports. 25(1). 80–94. 76 indexed citations
6.
Sanjabi, Shomyseh, Soyoung Oh, & Ming O. Li. (2017). Regulation of the Immune Response by TGF-β: From Conception to Autoimmunity and Infection. Cold Spring Harbor Perspectives in Biology. 9(6). a022236–a022236. 446 indexed citations breakdown →
7.
Oh, Soyoung, et al.. (2017). Foxp3-independent mechanism by which TGF-β controls peripheral T cell tolerance. Proceedings of the National Academy of Sciences. 114(36). E7536–E7544. 43 indexed citations
8.
Dadi, Saïda, Sagar Chhangawala, Benjamin M. Whitlock, et al.. (2016). Cancer Immunosurveillance by Tissue-Resident Innate Lymphoid Cells and Innate-like T Cells. Cell. 164(3). 365–377. 255 indexed citations
10.
Oh, Soyoung & Ming O. Li. (2013). TGF-β: Guardian of T Cell Function. The Journal of Immunology. 191(8). 3973–3979. 236 indexed citations
11.
Simons, Donald M., et al.. (2013). Autoreactive Th1 Cells Activate Monocytes To Support Regional Th17 Responses in Inflammatory Arthritis. The Journal of Immunology. 190(7). 3134–3141. 11 indexed citations
12.
Oh, Soyoung, Ronald H. Schwartz, & Nevil J. Singh. (2012). Development and Tolerization of Hyperacute Rejection in a Transgenic Mouse Graft Versus Host Model. Transplantation. 94(3). 234–240.
13.
Oh, Soyoung, et al.. (2012). Requirement for Diverse TCR Specificities Determines Regulatory T Cell Activity in a Mouse Model of Autoimmune Arthritis. The Journal of Immunology. 188(9). 4171–4180. 18 indexed citations
14.
Weiss, Jonathan M., Angelina M. Bilate, Michael Gobert, et al.. (2012). Neuropilin 1 is expressed on thymus-derived natural regulatory T cells, but not mucosa-generated induced Foxp3+ T reg cells. The Journal of Experimental Medicine. 209(10). 1723–1742. 480 indexed citations
15.
Picca, Cristina Cozzo, Donald M. Simons, Soyoung Oh, et al.. (2011). CD4 + CD25 + Foxp3 + regulatory T cell formation requires more specific recognition of a self-peptide than thymocyte deletion. Proceedings of the National Academy of Sciences. 108(36). 14890–14895. 33 indexed citations
16.
Simons, Donald M., Cristina Cozzo Picca, Soyoung Oh, et al.. (2010). How specificity for self-peptides shapes the development and function of regulatory T cells. Journal of Leukocyte Biology. 88(6). 1099–1107. 26 indexed citations
17.
Picca, Cristina Cozzo, et al.. (2009). Thymocyte deletion can bias Treg formation toward low‐abundance self‐peptide. European Journal of Immunology. 39(12). 3301–3306. 22 indexed citations
18.
Oh, Soyoung, Andrew L. Rankin, & Andrew J. Caton. (2009). CD4+CD25+regulatory T cells in autoimmune arthritis. Immunological Reviews. 233(1). 97–111. 49 indexed citations
19.
Feng, Xiaoming, Gregory C. Ippolito, Lifeng Tian, et al.. (2009). Foxp1 is an essential transcriptional regulator for the generation of quiescent naive T cells during thymocyte development. Blood. 115(3). 510–518. 97 indexed citations
20.
Rankin, Andrew L., Amy J. Reed, Soyoung Oh, et al.. (2008). CD4+ T Cells Recognizing a Single Self-Peptide Expressed by APCs Induce Spontaneous Autoimmune Arthritis. The Journal of Immunology. 180(2). 833–841. 22 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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