Jongsun Jung

12.7k total citations
25 papers, 726 citations indexed

About

Jongsun Jung is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Jongsun Jung has authored 25 papers receiving a total of 726 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Genetics and 5 papers in Cancer Research. Recurrent topics in Jongsun Jung's work include Cancer Genomics and Diagnostics (4 papers), Genomics and Rare Diseases (3 papers) and Genetic Associations and Epidemiology (3 papers). Jongsun Jung is often cited by papers focused on Cancer Genomics and Diagnostics (4 papers), Genomics and Rare Diseases (3 papers) and Genetic Associations and Epidemiology (3 papers). Jongsun Jung collaborates with scholars based in South Korea, United States and Australia. Jongsun Jung's co-authors include Byung Kook Lee, Hyun‐Jin Yang, Hyejin Park, Seungju Lee, Jaemin Shin, Hyung‐Lae Kim, Joohon Sung, Sunho Lee, Han‐Na Kim and Yangrae Cho and has published in prestigious journals such as Nucleic Acids Research, Blood and PLoS ONE.

In The Last Decade

Jongsun Jung

24 papers receiving 713 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jongsun Jung South Korea 12 413 134 128 97 84 25 726
J.M. Krahn United States 19 648 1.6× 51 0.4× 45 0.4× 39 0.4× 67 0.8× 42 931
David A. Scott United States 19 979 2.4× 320 2.4× 47 0.4× 121 1.2× 94 1.1× 50 1.5k
Yan Yuan Tseng United States 14 441 1.1× 73 0.5× 53 0.4× 106 1.1× 16 0.2× 37 548
Stefan Platz United Kingdom 9 377 0.9× 122 0.9× 75 0.6× 12 0.1× 94 1.1× 14 707
Jani Saarela Finland 19 583 1.4× 151 1.1× 80 0.6× 39 0.4× 113 1.3× 45 999
Isabell Bludau Germany 19 1.2k 3.0× 42 0.3× 58 0.5× 55 0.6× 95 1.1× 28 1.6k
Lijun Quan China 10 421 1.0× 82 0.6× 69 0.5× 35 0.4× 53 0.6× 29 543
Ashwini Patil Japan 20 1.2k 2.9× 157 1.2× 70 0.5× 127 1.3× 133 1.6× 52 1.5k
Justin Bo‐Kai Hsu Taiwan 18 887 2.1× 36 0.3× 61 0.5× 22 0.2× 91 1.1× 28 1.4k
Xiang Wu China 19 456 1.1× 78 0.6× 76 0.6× 25 0.3× 113 1.3× 46 886

Countries citing papers authored by Jongsun Jung

Since Specialization
Citations

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

Fields of papers citing papers by Jongsun Jung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jongsun Jung

This figure shows the co-authorship network connecting the top 25 collaborators of Jongsun Jung. A scholar is included among the top collaborators of Jongsun 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 Jongsun Jung. Jongsun Jung 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.
Jung, Jongsun, Eun Ju Kim, Won Ho Kim, et al.. (2023). Nitrosylation of β2-Tubulin Promotes Microtubule Disassembly and Differentiated Cardiomyocyte Beating in Ischemic Mice. Tissue Engineering and Regenerative Medicine. 20(6). 921–937.
2.
Lee, Sunho, et al.. (2018). Integrated genome sizing (IGS) approach for the parallelization of whole genome analysis. BMC Bioinformatics. 19(1). 462–462. 1 indexed citations
3.
Park, Hyejin, et al.. (2018). Cancer Drug Response Profile scan (CDRscan): A Deep Learning Model That Predicts Drug Effectiveness from Cancer Genomic Signature. Scientific Reports. 8(1). 8857–8857. 223 indexed citations
4.
Heo, Seong Gu, Youngil Koh, Jong-Kwang Kim, et al.. (2017). Identification of somatic mutations using whole-exome sequencing in Korean patients with acute myeloid leukemia. BMC Medical Genetics. 18(1). 23–23. 4 indexed citations
5.
Kim, Min Ho, et al.. (2017). Prevalence of Rare Genetic Variations and Their Implications in NGS-data Interpretation. Scientific Reports. 7(1). 9810–9810. 14 indexed citations
6.
Ka, Sojeong, Sunho Lee, Yangrae Cho, et al.. (2017). HLAscan: genotyping of the HLA region using next-generation sequencing data. BMC Bioinformatics. 18(1). 258–258. 75 indexed citations
7.
Lee, Jungmin, Jongsun Jung, In-Joong Kim, et al.. (2015). Genetic characterization of porcine epidemic diarrhea virus in Korea from 1998 to 2013. Archives of Virology. 160(4). 1055–1064. 56 indexed citations
8.
Jeong, Changhoon, Jae Young Lee, Ji‐Yeon Kim, et al.. (2014). Novel COL9A3 mutation in a family diagnosed with multiple epiphyseal dysplasia: a case report. BMC Musculoskeletal Disorders. 15(1). 371–371. 10 indexed citations
10.
Park, Edmond Changkyun, Jongsun Jung, Seung Il Kim, et al.. (2013). Differential Expression of MicroRNAs in Patients with Glioblastoma after Concomitant Chemoradiotherapy. OMICS A Journal of Integrative Biology. 17(5). 259–268. 10 indexed citations
11.
Jung, Jongsun, Yoon Shin Cho, Ji Hee Oh, et al.. (2010). Gene Flow between the Korean Peninsula and Its Neighboring Countries. PLoS ONE. 5(7). e11855–e11855. 12 indexed citations
12.
Hong, Kyung‐Won, Hyun‐Seok Jin, Yun Sang Cho, et al.. (2010). Non-synonymous single-nucleotide polymorphisms associated with blood pressure and hypertension. Journal of Human Hypertension. 24(11). 763–774. 39 indexed citations
13.
Lee, Hye‐Kyung, et al.. (2008). Allelic frequencies and heterozygosities of microsatellite markers covering the whole genome in the Korean. Journal of Human Genetics. 53(3). 254–266. 3 indexed citations
14.
Kim, Heeyeon, Hyun-Jin Park, Young‐Eun Cho, et al.. (2008). Evaluation of Influent Water Quality Using Indicator Microorganisms in Lake Shiwha. Korean Journal of Environmental Health Sciences. 34(1). 86–94. 2 indexed citations
15.
Hwang, Jooyeon, Hye‐Ja Lee, Mi‐Hyun Park, et al.. (2007). Single nucleotide polymorphisms in bone turnover-related genes in Koreans: ethnic differences in linkage disequilibrium and haplotype. BMC Medical Genetics. 8(1). 70–70. 5 indexed citations
16.
Kim, Hyo‐Bin, Yong‐Chul Lee, So‐Yeon Lee, et al.. (2006). Gene–gene interaction between IL-13 and IL-13Rα1 is associated with total IgE in Korean children with atopic asthma. Journal of Human Genetics. 51(12). 1055–1062. 41 indexed citations
17.
Kim, Sang Wun, Jongsun Jung, Kwang-Soo Lee, et al.. (2005). Structural and functional analyses of mutations of the human phenylalanine hydroxylase gene. Clinica Chimica Acta. 365(1-2). 279–287. 24 indexed citations
18.
Jung, Jongsun & Byung Kook Lee. (2001). Circularly permuted proteins in the protein structure database. Protein Science. 10(9). 1881–1886. 55 indexed citations
19.
Jung, Jongsun & Byung Kook Lee. (2000). Protein structure alignment using environmental profiles. Protein Engineering Design and Selection. 13(8). 535–543. 97 indexed citations
20.
Jung, Jongsun & Byung Kook Lee. (2000). Use of residue pairs in protein sequence‐sequence and sequence‐structure alignments. Protein Science. 9(8). 1576–1588. 11 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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