Dae‐Soon Son

1.4k total citations
43 papers, 785 citations indexed

About

Dae‐Soon Son is a scholar working on Cancer Research, Molecular Biology and Oncology. According to data from OpenAlex, Dae‐Soon Son has authored 43 papers receiving a total of 785 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cancer Research, 21 papers in Molecular Biology and 13 papers in Oncology. Recurrent topics in Dae‐Soon Son's work include Cancer Genomics and Diagnostics (17 papers), Lung Cancer Treatments and Mutations (6 papers) and Genomics and Rare Diseases (5 papers). Dae‐Soon Son is often cited by papers focused on Cancer Genomics and Diagnostics (17 papers), Lung Cancer Treatments and Mutations (6 papers) and Genomics and Rare Diseases (5 papers). Dae‐Soon Son collaborates with scholars based in South Korea, United States and United Kingdom. Dae‐Soon Son's co-authors include Woong‐Yang Park, Donghyun Park, Hyo Jeong Jeon, Yeon Jeong Kim, Gahee Park, Jinseon Lee, Hae‐Ock Lee, Jhingook Kim, Woosung Chung and Hye Hyeon Eum and has published in prestigious journals such as Cancer Research, Scientific Reports and Genome Research.

In The Last Decade

Dae‐Soon Son

39 papers receiving 767 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dae‐Soon Son South Korea 16 400 303 201 156 82 43 785
Kaiyan Yang China 16 437 1.1× 315 1.0× 190 0.9× 122 0.8× 58 0.7× 41 773
Chiara Maura Ciniselli Italy 18 407 1.0× 365 1.2× 235 1.2× 131 0.8× 124 1.5× 68 803
Kelly B. Engel United States 9 395 1.0× 304 1.0× 245 1.2× 137 0.9× 84 1.0× 13 780
Hye Won Lee South Korea 16 468 1.2× 387 1.3× 189 0.9× 110 0.7× 143 1.7× 78 964
Sílvia Cabrera Spain 19 318 0.8× 246 0.8× 145 0.7× 116 0.7× 45 0.5× 61 951
Brendan Pang Singapore 16 283 0.7× 190 0.6× 189 0.9× 184 1.2× 107 1.3× 30 648
Chenkai Ma Australia 12 518 1.3× 319 1.1× 144 0.7× 106 0.7× 40 0.5× 27 754
Qinghua Min China 13 572 1.4× 349 1.2× 121 0.6× 98 0.6× 50 0.6× 22 935
Youn Jin Choi South Korea 15 294 0.7× 204 0.7× 152 0.8× 87 0.6× 84 1.0× 52 792
Nathan Hunkapiller United States 9 354 0.9× 460 1.5× 195 1.0× 176 1.1× 88 1.1× 13 1.1k

Countries citing papers authored by Dae‐Soon Son

Since Specialization
Citations

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

Fields of papers citing papers by Dae‐Soon Son

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae‐Soon Son. 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 Dae‐Soon Son. The network helps show where Dae‐Soon Son may publish in the future.

Co-authorship network of co-authors of Dae‐Soon Son

This figure shows the co-authorship network connecting the top 25 collaborators of Dae‐Soon Son. A scholar is included among the top collaborators of Dae‐Soon Son 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 Dae‐Soon Son. Dae‐Soon Son 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
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Son, Dae‐Soon, et al.. (2024). A Longitudinal Study Investigating Whether Chronic Rhinosinusitis Influences the Subsequent Risk of Developing Dementia. Journal of Personalized Medicine. 14(11). 1081–1081.
4.
Son, Dae‐Soon, Yoon‐La Choi, Ji Eun Park, et al.. (2023). Clinical Validation of the Unparalleled Sensitivity of the Novel Allele-Discriminating Priming System Technology–Based EGFR Mutation Assay in Patients with Operable Non–Small Cell Lung Cancer. Cancer Research and Treatment. 56(1). 81–91. 2 indexed citations
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An, Minae, Dae‐Soon Son, Jinhyuk Choi, et al.. (2022). Comparison of cell type distribution between single-cell and single-nucleus RNA sequencing: enrichment of adherent cell types in single-nucleus RNA sequencing. Experimental & Molecular Medicine. 54(12). 2128–2134. 20 indexed citations
7.
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
8.
Hur, Joon Young, Yeon Jeong Kim, Sang Eun Yoon, et al.. (2020). Plasma cell-free DNA is a prognostic biomarker for survival in patients with aggressive non-Hodgkin lymphomas. Annals of Hematology. 99(6). 1293–1302. 19 indexed citations
9.
You, Seng Chan, Yu Rang Park, Jin Roh, et al.. (2019). Genomic Common Data Model for Seamless Interoperation of Biomedical Data in Clinical Practice: Retrospective Study. Journal of Medical Internet Research. 21(3). e13249–e13249. 18 indexed citations
10.
Park, Gahee, Joo Kyung Park, Dae‐Soon Son, et al.. (2018). Utility of targeted deep sequencing for detecting circulating tumor DNA in pancreatic cancer patients. Scientific Reports. 8(1). 43 indexed citations
11.
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
12.
Lee, Chung, Joon Seol Bae, Gyu Ha Ryu, et al.. (2017). A Method to Evaluate the Quality of Clinical Gene-Panel Sequencing Data for Single-Nucleotide Variant Detection. Journal of Molecular Diagnostics. 19(5). 651–658. 15 indexed citations
13.
Kim, Jin‐Seog, Insuk Sohn, Dae‐Soon Son, et al.. (2013). Prediction of a time-to-event trait using genome wide SNP data. BMC Bioinformatics. 14(1). 58–58. 3 indexed citations
14.
Yi, Chin A, Dae‐Soon Son, Jinseon Lee, et al.. (2008). Prediction of lymph node metastasis using the combined criteria of helical CT and mRNA expression profiling for non-small cell lung cancer. Lung Cancer. 60(2). 264–270. 8 indexed citations
15.
Kim, Bumjin, Hyun Joo Lee, Hye Young Choi, et al.. (2007). Clinical Validity of the Lung Cancer Biomarkers Identified by Bioinformatics Analysis of Public Expression Data. Cancer Research. 67(15). 7431–7438. 78 indexed citations
16.
Lee, Won Suk, Hee Jung Shin, Seong Hyeon Yun, et al.. (2007). Identification of Differentially Expressed Genes in Microsatellite Stable HNPCC and Sporadic Colon Cancer. Journal of Surgical Research. 144(1). 29–35. 22 indexed citations
17.
Choi, Hye Young, Jinseon Lee, Dae‐Soon Son, et al.. (2007). Elevated activities of MMP‐2 in the non‐tumorous lung tissues of curatively resected stage I NSCLC patients are associated with tumor recurrence and a poor survival. Journal of Surgical Oncology. 95(4). 337–346. 9 indexed citations
18.
Kim, Tae‐Joong, Jung‐Joo Choi, Woo Young Kim, et al.. (2007). Gene expression profiling for the prediction of lymph node metastasis in patients with cervical cancer. Cancer Science. 99(1). 31–38. 35 indexed citations
19.
Son, Dae‐Soon, Jinseon Lee, Kyung‐Ah Kim, et al.. (2006). The Signature from Messenger RNA Expression Profiling Can Predict Lymph Node Metastasis with High Accuracy for Non-small Cell Lung Cancer. Journal of Thoracic Oncology. 1(7). 622–628. 9 indexed citations
20.
Son, Dae‐Soon, Hyesook Lee, Min Sup Song, et al.. (2005). RASSF1A is not appropriate as an early detection marker or a prognostic marker for non‐small cell lung cancer. International Journal of Cancer. 115(4). 575–581. 18 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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