Jun Chang

4.1k total citations · 1 hit paper
122 papers, 3.2k citations indexed

About

Jun Chang is a scholar working on Epidemiology, Immunology and Molecular Biology. According to data from OpenAlex, Jun Chang has authored 122 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Epidemiology, 48 papers in Immunology and 24 papers in Molecular Biology. Recurrent topics in Jun Chang's work include Respiratory viral infections research (37 papers), Immunotherapy and Immune Responses (26 papers) and Immune Cell Function and Interaction (25 papers). Jun Chang is often cited by papers focused on Respiratory viral infections research (37 papers), Immunotherapy and Immune Responses (26 papers) and Immune Cell Function and Interaction (25 papers). Jun Chang collaborates with scholars based in South Korea, China and United States. Jun Chang's co-authors include Thomas J. Braciale, Young Chul Sung, Youngjoo Choi, Do‐Hyung Kim, Man Ki Song, Sang‐Jun Ha, Anon Srikiatkhachorn, Joo‐Young Kim, Kwan Yong Choi and Kyou‐Hoon Han and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Jun Chang

120 papers receiving 3.2k citations

Hit Papers

In vivo delivery of CRISPR-Cas9 using lipid nanoparticles... 2022 2026 2023 2024 2022 40 80 120
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.

  1. In vivo delivery of CRISPR-Cas9 using lipid nanoparticles enables antithrombin gene editing for sustainable hemophilia A and B therapy
    2022 130 citations M. Kim, Michaela Jeong et al. Science Advances profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Chang South Korea 32 1.2k 1.1k 1.0k 605 503 122 3.2k
Donald D. Anthony United States 36 1.1k 1.0× 1.3k 1.2× 756 0.7× 632 1.0× 433 0.9× 128 3.9k
Fang Guo China 29 935 0.8× 599 0.6× 784 0.8× 401 0.7× 548 1.1× 97 2.7k
Lei Li China 30 974 0.8× 553 0.5× 802 0.8× 589 1.0× 179 0.4× 192 2.9k
Hans-Heinrich Hoffmann United States 22 1.2k 1.0× 1.1k 1.1× 651 0.6× 1.0k 1.7× 255 0.5× 36 3.0k
Elisa Vicenzi Italy 36 783 0.7× 2.0k 1.9× 983 1.0× 1.2k 2.0× 478 1.0× 136 4.2k
Nathaniel J. Moorman United States 31 1.3k 1.2× 797 0.7× 1.6k 1.5× 630 1.0× 457 0.9× 90 3.3k
Sun Park South Korea 29 1.3k 1.1× 1.1k 1.0× 564 0.5× 332 0.5× 455 0.9× 111 3.3k
Nathalie Grandvaux Canada 36 1.5k 1.3× 3.8k 3.5× 1.2k 1.2× 1.0k 1.7× 918 1.8× 80 5.4k
Timo Sareneva Finland 30 1.1k 0.9× 2.6k 2.4× 901 0.9× 304 0.5× 692 1.4× 36 3.8k

Countries citing papers authored by Jun Chang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Chang. A scholar is included among the top collaborators of Jun Chang 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 Jun Chang. Jun Chang 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.
Cho, Byoung-Kyu, Eugene C. Yi, Joon‐Yong An, et al.. (2025). CD99-mediated immunological synapse formation potentiates CAR-T cell function. Nature Communications. 16(1). 7987–7987.
2.
Ye, Ying, et al.. (2024). Chemical Constituents from Ampelopsis grossedentata and Their Inhibitory Effects on Th17 Cell Differentiation. Chemistry of Natural Compounds. 60(3). 515–516. 1 indexed citations
3.
4.
5.
Kim, M., Michaela Jeong, Yeji Lee, et al.. (2022). In vivo delivery of CRISPR-Cas9 using lipid nanoparticles enables antithrombin gene editing for sustainable hemophilia A and B therapy. Science Advances. 8(3). eabj6901–eabj6901. 130 indexed citations breakdown →
6.
Lee, Young-Kwan, Woojin Kim, Ji Young Lim, et al.. (2021). IDO1 scavenges reactive oxygen species in myeloid-derived suppressor cells to prevent graft-versus-host disease. Proceedings of the National Academy of Sciences. 118(10). 27 indexed citations
7.
Lee, Hyo‐Jeong, Jeong-Yoon Lee, Minhee Park, Joo‐Young Kim, & Jun Chang. (2017). Monoclonal Antibody against G Glycoprotein Increases Respiratory Syncytial Virus Clearance In Vivo and Prevents Vaccine-Enhanced Diseases. PLoS ONE. 12(1). e0169139–e0169139. 26 indexed citations
8.
Ban, Young Ho, Sang Hwan Seo, Seok‐min Kim, et al.. (2017). miR-150-Mediated Foxo1 Regulation Programs CD8+ T Cell Differentiation. Cell Reports. 20(11). 2598–2611. 36 indexed citations
9.
Lee, Eun‐Young, et al.. (2016). Sublingual immunization with Japanese encephalitis virus vaccine effectively induces immunity through both cellular and humoral immune responses in mice. Microbiology and Immunology. 60(12). 846–853. 8 indexed citations
10.
11.
Peng, Xindong, et al.. (2014). Observational Calibration of Numerical Weather Prediction with Anomaly Integration. EGUGA. 5026. 2 indexed citations
12.
Firdous, Jannatul, Mohammad Ariful Islam, Byoung-Shik Shim, et al.. (2014). Induction of long-term immunity against respiratory syncytial virus glycoprotein by an osmotic polymeric nanocarrier. Acta Biomaterialia. 10(11). 4606–4617. 17 indexed citations
13.
Cheon, In Su, Semi Rho, Hee Joo Kim, et al.. (2013). Neonatal Immunization with Respiratory Syncytial Virus Glycoprotein Fragment Induces Protective Immunity in the Presence of Maternal Antibodies in Mice. Viral Immunology. 26(4). 268–276. 9 indexed citations
14.
Youn, Ui Joung, Yoo Jin Lee, Young Min Son, et al.. (2011). Anti-respiratory syncytial virus (RSV) activity of timosaponin A-III from the rhizomes of Anemarrhena asphodeloides. Journal of Medicinal Plants Research. 5(7). 1062–1065. 10 indexed citations
15.
Kim, Kyung‐Hyo, et al.. (2011). Evaluation of Protective Efficacy of Respiratory Syncytial Virus Vaccine against A and B Subgroup Human Isolates in Korea. PLoS ONE. 6(9). e23797–e23797. 13 indexed citations
16.
17.
Chang, Jun, et al.. (2004). Improved Effector Activity and Memory CD8 T Cell Development by IL-2 Expression during Experimental Respiratory Syncytial Virus Infection. The Journal of Immunology. 172(1). 503–508. 39 indexed citations
18.
Lee, Si Hyung, et al.. (2001). Structural Origin for the Transcriptional Activity of Human p53. BMB Reports. 34(1). 73–79. 3 indexed citations
19.
Chang, Jun, Anon Srikiatkhachorn, & Thomas J. Braciale. (2001). Visualization and Characterization of Respiratory Syncytial Virus F-Specific CD8+ T Cells During Experimental Virus Infection. The Journal of Immunology. 167(8). 4254–4260. 101 indexed citations
20.
Baek, Won‐Ki, et al.. (2001). HCV core protein modulates Rb pathway through pRb down-regulation and E2F-1 up-regulation. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1538(1). 59–66. 50 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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