Dongmin Jung

5.8k total citations · 1 hit paper
16 papers, 3.0k citations indexed

About

Dongmin Jung is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dongmin Jung has authored 16 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Pulmonary and Respiratory Medicine, 5 papers in Oncology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dongmin Jung's work include Lung Cancer Treatments and Mutations (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Advanced Statistical Methods and Models (2 papers). Dongmin Jung is often cited by papers focused on Lung Cancer Treatments and Mutations (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Advanced Statistical Methods and Models (2 papers). Dongmin Jung collaborates with scholars based in South Korea, United States and Ethiopia. Dongmin Jung's co-authors include Runan Yao, Xijin Ge, Jong‐Min Kim, Jae Woo Choi, Kayoung Park, Seonwoo Min, Sungroh Yoon, Hui Kwon Kim, Jinman Park and Seokjoong Kim and has published in prestigious journals such as Cell, Journal of Clinical Oncology and Bioinformatics.

In The Last Decade

Dongmin Jung

15 papers receiving 3.0k 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.

ShinyGO: a graphical gene-set enrichment tool for animals and plants

2019 2.7k citations Xijin Ge, Dongmin Jung et al. Bioinformatics profile →

Peers

Dongmin Jung

MB

PS

GENET

CR

IMMUN

Cory Brouwer United States

Runan Yao United States

John Braisted United States

Seiya Imoto Japan

Francisco García‐García Spain

Jing Lü China

Yu Chen China

Chen Meng China

Zihao He China

Chittibabu Guda United States

Cory Brouwer United States

Dongmin Jung

1.5k ×1.0

MB

565 ×1.1

PS

378 ×1.1

GENET

349 ×1.0

CR

291 ×0.9

IMMUN

Citations per year, relative to Dongmin Jung Dongmin Jung (= 1×) peers Cory Brouwer

Countries citing papers authored by Dongmin Jung

Since Specialization

Citations

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

Fields of papers citing papers by Dongmin Jung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongmin Jung

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

1.

Kim, Chang-Hwan, Dongmin Jung, Min Cheol Han, et al.. (2024). Evaluation of the deliverability of dynamic conformal arc therapy (DCAT) by gantry wobble and its influence on dose. Scientific Reports. 14(1). 7134–7134. 2 indexed citations

2.

Lim, Jung Min, Inkyung Jung, Seok‐Jae Heo, et al.. (2021). Recording of elapsed time and temporal information about biological events using Cas9. Cell. 184(4). 1047–1063.e23. 24 indexed citations

3.

Kim, Min Hwan, Jae Hwan Kim, Jae Woo Choi, et al.. (2020). Molecular subtypes of oropharyngeal cancer show distinct immune microenvironment related with immune checkpoint blockade response. British Journal of Cancer. 122(11). 1649–1660. 17 indexed citations

4.

Park, Kayoung, Dongmin Jung, & Jong‐Min Kim. (2020). Control charts based on randomized quantile residuals. Applied Stochastic Models in Business and Industry. 36(4). 716–729. 27 indexed citations

5.

Ge, Xijin, Dongmin Jung, & Runan Yao. (2019). ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics. 36(8). 2628–2629. 2659 indexed citations breakdown →

6.

Lim, Sun Min, Jae Woo Choi, Min Hee Hong, et al.. (2019). Indoor radon exposure increases tumor mutation burden in never-smoker patients with lung adenocarcinoma. Lung Cancer. 131. 139–146. 26 indexed citations

7.

Kim, Hui Kwon, Younggwang Kim, Sungtae Lee, et al.. (2019). SpCas9 activity prediction by DeepSpCas9, a deep learning–based model with high generalization performance. Science Advances. 5(11). eaax9249–eaax9249. 140 indexed citations

8.

Kim, Seok‐Young, Donghwi Kim, Mi Ran Yun, et al.. (2019). Patient-Derived Cells to Guide Targeted Therapy for Advanced Lung Adenocarcinoma. Scientific Reports. 9(1). 19909–19909. 27 indexed citations

9.

Choi, Jae Woo, Min Hee Hong, Dongmin Jung, et al.. (2019). Molecular characterization of lung adenocarcinoma from Korean patients using next generation sequencing. PLoS ONE. 14(11). e0224379–e0224379. 13 indexed citations

10.

Ahn, Beung‐Chul, Kyoung‐Ho Pyo, Dongmin Jung, et al.. (2019). Comprehensive analysis of the characteristics and treatment outcomes of patients with non-small cell lung cancer treated with anti-PD-1 therapy in real-world practice. Journal of Cancer Research and Clinical Oncology. 145(6). 1613–1623. 74 indexed citations

11.

Ahn, Beung‐Chul, Kyoung‐Ho Pyo, Dongmin Jung, et al.. (2019). A machine learning based prediction model of anti-PD-1 therapy response using noninvasive clinical information and blood markers of lung cancer patients.. Journal of Clinical Oncology. 37(15_suppl). e14138–e14138. 1 indexed citations

12.

Pyo, Kyoung‐Ho, Beung‐Chul Ahn, Dongmin Jung, et al.. (2019). Abstract 683: A machine learning based clinical decision support system (CDSS) for anti-PD-1 therapy using non-invasive blood marker and clinical information for lung cancer patients. Cancer Research. 79(13_Supplement). 683–683. 1 indexed citations

13.

Pyo, Kyoung‐Ho, Beung‐Chul Ahn, Dongmin Jung, et al.. (2019). Abstract 683: A machine learning based clinical decision support system (CDSS) for anti-PD-1 therapy using non-invasive blood marker and clinical information for lung cancer patients. 683–683. 1 indexed citations

14.

Park, Kayoung, Jong‐Min Kim, & Dongmin Jung. (2018). GLM‐based statistical control r‐charts for dispersed count data with multicollinearity between input variables. Quality and Reliability Engineering International. 34(6). 1103–1109. 26 indexed citations

15.

Mendel, V. E., Dongmin Jung, Hanne Scholz, & H Heymann. (1986). ["One-shot" prophylaxis in elective colon surgery. Effect of pharmacokinetics and action spectrum].. PubMed. 53(3). 351–61.

16.

Jung, Dongmin, et al.. (1981). [Pneumoperitoneum after lavage without perforation of a hollow organ].. PubMed. 32(8). 256–256. 1 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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