Hyeyoon Kim

571 total citations
34 papers, 392 citations indexed

About

Hyeyoon Kim is a scholar working on Molecular Biology, Spectroscopy and Psychiatry and Mental health. According to data from OpenAlex, Hyeyoon Kim has authored 34 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 10 papers in Spectroscopy and 8 papers in Psychiatry and Mental health. Recurrent topics in Hyeyoon Kim's work include Advanced Proteomics Techniques and Applications (10 papers), Tryptophan and brain disorders (7 papers) and Bipolar Disorder and Treatment (6 papers). Hyeyoon Kim is often cited by papers focused on Advanced Proteomics Techniques and Applications (10 papers), Tryptophan and brain disorders (7 papers) and Bipolar Disorder and Treatment (6 papers). Hyeyoon Kim collaborates with scholars based in South Korea, United States and Ethiopia. Hyeyoon Kim's co-authors include Dohyun Han, Joonho Park, Yeonjae Kim, Hyukmin Lee, So Yeon Kim, Moon‐Woo Seong, Han Suk Ryu, Youngsoo Kim, Hyebin Lee and Hyunsuk Shin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Hyeyoon Kim

30 papers receiving 390 citations

Peers

Hyeyoon Kim

SPECT

PRM

SURGE

Juan Ouyang China

Zhenguo Liu China

Stefan D. Jevtic Canada

Paul B. Dieffenbach United States

Weixing Hu China

Alexander Gratopp Germany

Angela L. Rachubinski United States

Julie A. Buckley United States

Leonie Beyer Germany

Richard Kirkland United States

Juan Ouyang China

Hyeyoon Kim

131 ×0.8

16 ×0.2

SPECT

48 ×0.8

PRM

13 ×0.3

SURGE

25 ×0.5

Citations per year, relative to Hyeyoon Kim Hyeyoon Kim (= 1×) peers Juan Ouyang

Countries citing papers authored by Hyeyoon Kim

Since Specialization

Citations

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

Fields of papers citing papers by Hyeyoon Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyeyoon Kim

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

All Works

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20 of 20 papers shown

Hwang, Soo‐Yeon, Seojeong Park, Yi Liu, et al.. (2025). Targeting the HER2-ELF3-KRAS axis: a novel therapeutic strategy for KRASG13D colorectal cancer. Molecular Cancer. 24(1). 139–139. 1 indexed citations

Walukiewicz, Hanna E., Meagan Burnet, Hyeyoon Kim, et al.. (2024). Regulation of bacterial stringent response by an evolutionarily conserved ribosomal protein L11 methylation. mBio. 15(10). e0177324–e0177324. 1 indexed citations

Park, Hye Eun, Dohyun Han, Jae Seok Lee, et al.. (2024). Comparison of Breast Fine-Needle Aspiration Cytology and Tissue Sampling for High-Throughput Proteomic Analysis and Cancer Biomarker Detection. Pathobiology. 91(5). 359–369. 3 indexed citations

Tsai, Chia‐Feng, Chuan‐Chih Hsu, Yi‐Ting Wang, Hyeyoon Kim, & Tao Liu. (2024). A Tip-Based Workflow for Sensitive IMAC-Based Low Nanogram Level Phosphoproteomics. Methods in molecular biology. 2823. 129–140.

Koh, Jiwon, Dabin Jeong, Soo Young Park, et al.. (2024). Identification of VWA5A as a novel biomarker for inhibiting metastasis in breast cancer by machine-learning based protein prioritization. Scientific Reports. 14(1). 2459–2459.

Ahn, Soo Hyun, Yoonhyuk Jang, Bum‐Sup Jang, et al.. (2024). Multi-omic insights into molecular mechanism and therapeutic targets in spinocerebellar ataxia type 7. Molecular Therapy — Nucleic Acids. 36(1). 102414–102414. 1 indexed citations

Han, Dohyun, Kyung Sue Hong, Kyooseob Ha, et al.. (2024). Integrated proteomic and genomic analysis to identify predictive biomarkers for valproate response in bipolar disorder: a 6-month follow-up study. International Journal of Bipolar Disorders. 12(1). 19–19. 1 indexed citations

Jung, Jin Woo, Hyeyoon Kim, Joonho Park, et al.. (2023). In-depth proteome analysis of brain tissue from Ewsr1 knockout mouse by multiplexed isobaric tandem mass tag labeling. Scientific Reports. 13(1). 15261–15261.

Kim, Minah, Se Hyun Kim, Junhee Lee, et al.. (2023). Proteomic profiling in the progression of psychosis: Analysis of clinical high-risk, first episode psychosis, and healthy controls. Journal of Psychiatric Research. 169. 264–271. 2 indexed citations

10.

Han, Dohyun, et al.. (2022). The proteomic landscape shows oncologic relevance in cystitis glandularis. Journal of Pathology and Translational Medicine. 57(1). 67–74. 1 indexed citations

11.

Han, Dohyun, Sang Jin Rhee, Jayoun Kim, et al.. (2022). Alterations in blood proteins in the prodromal stage of bipolar II disorders. Scientific Reports. 12(1). 3174–3174. 5 indexed citations

12.

Rhee, Sang Jin, Jayoun Kim, Yunna Lee, et al.. (2021). Plasma proteomic data in bipolar II disorders and major depressive disorders. SHILAP Revista de lepidopterología. 39. 107495–107495. 1 indexed citations

13.

Kim, Jung Hee, Hyeyoon Kim, Seong‐Ik Kim, et al.. (2021). In-depth proteomic profiling captures subtype-specific features of craniopharyngiomas. Scientific Reports. 11(1). 21206–21206. 7 indexed citations

14.

Kim, Hye-Young, Sang Jin Rhee, Dohyun Han, et al.. (2021). Identification of altered protein expression in major depressive disorder and bipolar disorder patients using liquid chromatography–tandem mass spectrometry. Psychiatry Research. 299. 113850–113850. 15 indexed citations

15.

Rhee, Sang Jin, Jayoun Kim, Yunna Lee, et al.. (2021). Predictive protein markers for depression severity in mood disorders: A preliminary trans-diagnostic approach study. Journal of Psychiatric Research. 142. 63–72. 9 indexed citations

16.

Park, Joonho, Hyeyoon Kim, So Yeon Kim, et al.. (2020). In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients. Scientific Reports. 10(1). 22418–22418. 77 indexed citations

17.

Shin, Jung-Won, Hyeyoon Kim, Kwang‐Hyun Baek, et al.. (2020). Bioinformatic analysis of proteomic data for iron, inflammation, and hypoxic pathways in restless legs syndrome. Sleep Medicine. 75. 448–455. 23 indexed citations

18.

Min, Hophil, et al.. (2019). Quantitative Proteome Analysis of Brain Subregions and Spinal Cord from Experimental Autoimmune Encephalomyelitis Mice by TMT‐Based Mass Spectrometry. PROTEOMICS. 19(5). e1800355–e1800355. 19 indexed citations

19.

Kim, Hyeyoon, Hye‐Yeon Kim, Seong‐Ho Kong, et al.. (2018). Comparative proteomic analysis of human malignant ascitic fluids for the development of gastric cancer biomarkers. Clinical Biochemistry. 56. 55–61. 19 indexed citations

20.

Lee, Hyebin, Kwangsoo Kim, Jongmin Jacob Woo, et al.. (2018). Quantitative Proteomic Analysis Identifies AHNAK (Neuroblast Differentiation-associated Protein AHNAK) as a Novel Candidate Biomarker for Bladder Urothelial Carcinoma Diagnosis by Liquid-based Cytology. Molecular & Cellular Proteomics. 17(9). 1788–1802. 66 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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