Woosung Chung

3.0k total citations · 1 hit paper
8 papers, 1.2k citations indexed

About

Woosung Chung is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Woosung Chung has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Immunology. Recurrent topics in Woosung Chung's work include Single-cell and spatial transcriptomics (3 papers), Immune cells in cancer (3 papers) and Cancer Genomics and Diagnostics (3 papers). Woosung Chung is often cited by papers focused on Single-cell and spatial transcriptomics (3 papers), Immune cells in cancer (3 papers) and Cancer Genomics and Diagnostics (3 papers). Woosung Chung collaborates with scholars based in South Korea, United States and Ethiopia. Woosung Chung's co-authors include Hae‐Ock Lee, Woong‐Yang Park, Hye Hyeon Eum, Jeong Eon Lee, Sangmin Kim, Yeon Hee Park, Wonshik Han, Kyung Min Lee, Han‐Byoel Lee and Kyu-Tae Kim and has published in prestigious journals such as Nature Communications, PLoS ONE and Genome Research.

In The Last Decade

Woosung Chung

7 papers receiving 1.2k citations

Hit Papers

Single-cell RNA-seq enables comprehensive tumour and immu... 2017 2026 2020 2023 2017 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Woosung Chung South Korea 6 875 553 483 287 147 8 1.2k
Hye Hyeon Eum South Korea 9 839 1.0× 516 0.9× 460 1.0× 289 1.0× 117 0.8× 13 1.2k
Yuliana Tan United States 4 635 0.7× 342 0.6× 377 0.8× 238 0.8× 68 0.5× 5 971
Tobias Anzeneder Germany 12 631 0.7× 334 0.6× 554 1.1× 349 1.2× 131 0.9× 18 1.1k
Anuja Sathe United States 16 743 0.8× 355 0.6× 352 0.7× 267 0.9× 191 1.3× 37 1.2k
Reuben Moncada United States 4 791 0.9× 339 0.6× 318 0.7× 292 1.0× 75 0.5× 7 1.1k
Ayse Bassez Belgium 4 815 0.9× 462 0.8× 842 1.7× 659 2.3× 255 1.7× 8 1.5k
Ruby Wasti France 2 656 0.7× 292 0.5× 621 1.3× 707 2.5× 121 0.8× 2 1.3k
Phuong Dao United States 3 656 0.7× 293 0.5× 643 1.3× 739 2.6× 120 0.8× 7 1.3k
Veronique Neumeister United States 17 510 0.6× 319 0.6× 496 1.0× 92 0.3× 170 1.2× 35 968
Daphne Tsoucas United States 8 602 0.7× 249 0.5× 575 1.2× 565 2.0× 103 0.7× 8 1.2k

Countries citing papers authored by Woosung Chung

Since Specialization
Citations

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

Fields of papers citing papers by Woosung Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Woosung Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Woosung Chung. A scholar is included among the top collaborators of Woosung Chung 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 Woosung Chung. Woosung Chung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Kim, Yesol, Je Yeong Ko, Hyun Kyung Kong, et al.. (2024). Hypomethylation of ATP1A1 Is Associated with Poor Prognosis and Cancer Progression in Triple-Negative Breast Cancer. Cancers. 16(9). 1666–1666. 3 indexed citations
2.
Chung, Woosung, et al.. (2021). A Study on Detecting Mask Wearing Status using Ensemble based on Deep Learning. Journal of Digital Contents Society. 22(11). 1931–1939.
3.
Eum, Hye Hyeon, Minsuk Kwon, Daeun Ryu, et al.. (2020). Tumor-promoting macrophages prevail in malignant ascites of advanced gastric cancer. Experimental & Molecular Medicine. 52(12). 1976–1988. 68 indexed citations
4.
Lee, Hye Won, Woosung Chung, Hae‐Ock Lee, et al.. (2020). Single-cell RNA sequencing reveals the tumor microenvironment and facilitates strategic choices to circumvent treatment failure in a chemorefractory bladder cancer patient. Genome Medicine. 12(1). 47–47. 127 indexed citations
5.
Kim, Nayoung, Woosung Chung, Hye Hyeon Eum, Hae‐Ock Lee, & Woong‐Yang Park. (2019). Alternative polyadenylation of single cells delineates cell types and serves as a prognostic marker in early stage breast cancer. PLoS ONE. 14(5). e0217196–e0217196. 25 indexed citations
6.
Han, Kyung Yeon, Kyu‐Tae Kim, Je‐Gun Joung, et al.. (2017). SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells. Genome Research. 28(1). 75–87. 99 indexed citations
7.
Chung, Woosung, Hye Hyeon Eum, Hae‐Ock Lee, et al.. (2017). Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nature Communications. 8(1). 15081–15081. 691 indexed citations breakdown →
8.
Kim, Kyu‐Tae, Hye Won Lee, Hae‐Ock Lee, et al.. (2015). Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells. Genome Biology. 16(1). 127–127. 210 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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