Hyo‐Jeong Ban

513 total citations
22 papers, 299 citations indexed

About

Hyo‐Jeong Ban is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Hyo‐Jeong Ban has authored 22 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Genetics and 4 papers in Cancer Research. Recurrent topics in Hyo‐Jeong Ban's work include Genetic Associations and Epidemiology (4 papers), Genetic and phenotypic traits in livestock (3 papers) and Epigenetics and DNA Methylation (3 papers). Hyo‐Jeong Ban is often cited by papers focused on Genetic Associations and Epidemiology (4 papers), Genetic and phenotypic traits in livestock (3 papers) and Epigenetics and DNA Methylation (3 papers). Hyo‐Jeong Ban collaborates with scholars based in South Korea, United States and Switzerland. Hyo‐Jeong Ban's co-authors include Keun-Joon Park, Kyungsoo Oh, Jee Yeon Heo, Jung Kyoon Choi, Sang Cheol Kim, Jungmin Seo, Seong Beom Cho, Kyung‐Won Hong, Hyoung‐Sam Heo and Harikrishna Paik and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

In The Last Decade

Hyo‐Jeong Ban

20 papers receiving 295 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hyo‐Jeong Ban South Korea	8	131	72	39	37	31	22	299
Makrina Daniilidou Greece	11	122 0.9×	37 0.5×	16 0.4×	131 3.5×	20 0.6×	17	331
Mengting Li China	12	168 1.3×	61 0.8×	6 0.2×	20 0.5×	45 1.5×	47	341
Lauren C. Briere United States	10	103 0.8×	78 1.1×	7 0.2×	35 0.9×	10 0.3×	18	253
Min‐Tzu Lo United States	12	202 1.5×	145 2.0×	21 0.5×	132 3.6×	41 1.3×	25	527
Yuhong Li China	9	100 0.8×	60 0.8×	5 0.1×	66 1.8×	13 0.4×	22	378
Kang Wu China	6	96 0.7×	17 0.2×	13 0.3×	75 2.0×	14 0.5×	17	271
I‐Ya Chen Taiwan	11	134 1.0×	83 1.2×	17 0.4×	141 3.8×	15 0.5×	18	366
Satoru Ohtomo Japan	10	47 0.4×	25 0.3×	26 0.7×	23 0.6×	146 4.7×	21	395
Young‐Eun Cho United States	9	159 1.2×	14 0.2×	9 0.2×	28 0.8×	11 0.4×	24	349
Aki Ito Japan	9	123 0.9×	24 0.3×	11 0.3×	17 0.5×	17 0.5×	27	387

Countries citing papers authored by Hyo‐Jeong Ban

Since Specialization

Citations

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

Fields of papers citing papers by Hyo‐Jeong Ban

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hyo‐Jeong Ban. 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 Hyo‐Jeong Ban. The network helps show where Hyo‐Jeong Ban may publish in the future.

Co-authorship network of co-authors of Hyo‐Jeong Ban

This figure shows the co-authorship network connecting the top 25 collaborators of Hyo‐Jeong Ban. A scholar is included among the top collaborators of Hyo‐Jeong Ban 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 Hyo‐Jeong Ban. Hyo‐Jeong Ban 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:

20 of 20 papers shown

Ban, Hyo‐Jeong, et al.. (2025). Shared rare genetic variants in multiplex autism families suggest a social memory gene under selection. Scientific Reports. 15(1). 696–696.

Ban, Hyo‐Jeong, et al.. (2024). Exploring Stroke Risk through Mendelian Randomization: A Comprehensive Study Integrating Genetics and Metabolic Traits in the Korean Population. Biomedicines. 12(6). 1311–1311.

Cho, Hye‐Won, Hyo‐Jeong Ban, Hyun‐Seok Jin, Seongwon Cha, & Yong‐Bin Eom. (2023). Effect of genetic variants in UBE2O and TPK1 on facial morphology of Koreans. Forensic Sciences Research. 8(1). 62–69. 1 indexed citations

Park, Sang‐Min, et al.. (2023). Blood transcriptomic markers associated with immune abnormalities and sleep quality. Genes & Diseases. 11(6). 101105–101105. 2 indexed citations

Lee, Choong‐kun, Hong Jae Chon, Woo Sun Kwon, et al.. (2022). The UGT1A9*22 genotype identifies a high-risk group for irinotecan toxicity among gastric cancer patients. Genomics & Informatics. 20(3). e29–e29. 1 indexed citations

Park, Sang‐Min, et al.. (2022). Systematic Analysis of the Molecular Mechanisms of Cold and Hot Properties of Herbal Medicines. Plants. 11(7). 997–997. 7 indexed citations

Park, Sang‐Min, et al.. (2022). Investigation of prodromal features in metabolic syndrome based on transcriptome analysis. Genes & Diseases. 10(3). 708–711. 3 indexed citations

Baek, Su‐Jin, et al.. (2022). Genome-wide DNA methylation profiling reveals candidate biomarkers and probable molecular mechanism of metabolic syndrome. Genes & Diseases. 9(4). 833–836. 6 indexed citations

Liu, Dongjing, Hyo‐Jeong Ban, Myoung Keun Lee, et al.. (2021). PRICKLE1 × FOCAD Interaction Revealed by Genome-Wide vQTL Analysis of Human Facial Traits. Frontiers in Genetics. 12. 674642–674642. 5 indexed citations

10.

Baek, Su‐Jin, Hyo‐Jeong Ban, Sang‐Min Park, et al.. (2021). Circulating microRNAs as Potential Diagnostic Biomarkers for Poor Sleep Quality. Nature and Science of Sleep. Volume 13. 1001–1012. 8 indexed citations

11.

Park, Sunju, et al.. (2020). Perception on genetic testing in Korean medicine doctors: A mobile-based survey. Integrative Medicine Research. 10(2). 100643–100643. 1 indexed citations

12.

Hong, Kyung‐Won, et al.. (2020). KRGDB: the large-scale variant database of 1722 Koreans based on whole genome sequencing. Database. 2020. 56 indexed citations

13.

Sung, Min Kyung, et al.. (2019). Convolutional neural network model to predict causal risk factors that share complex regulatory features. Nucleic Acids Research. 47(22). e146–e146. 10 indexed citations

14.

Lee, Hae‐Young, et al.. (2019). The age distribution of facial metrics in two large Korean populations. Scientific Reports. 9(1). 14564–14564. 3 indexed citations

15.

Lee, Woojung, Hyo‐Jung Lee, Han Byul Jang, et al.. (2018). Asymmetric dimethylarginine (ADMA) is identified as a potential biomarker of insulin resistance in skeletal muscle. Scientific Reports. 8(1). 2133–2133. 38 indexed citations

16.

Paik, Harikrishna, et al.. (2014). Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditions. Journal of Translational Medicine. 12(1). 99–99. 23 indexed citations

17.

Ryu, Yeonhee, et al.. (2011). Histological Comparison Study with Primo Node and Immature Liver Tissue on Liver Surface in Rat. Korean Journal of Acupuncture. 28(1). 47–52. 1 indexed citations

18.

Ban, Hyo‐Jeong, et al.. (2011). Genetic and Metabolic Characterization of Insomnia. PLoS ONE. 6(4). e18455–e18455. 55 indexed citations

19.

Lee, Sung Won, et al.. (2010). The Induction Effect of Apoptosis in A549 Human Lung Cancer Cells by the Trichosanthes Kirilowii Pharmacopuncture Solution. Korean Journal of Acupuncture. 27(4). 15–23. 1 indexed citations

20.

Ban, Hyo‐Jeong, Jee Yeon Heo, Kyungsoo Oh, & Keun-Joon Park. (2010). Identification of Type 2 Diabetes-associated combination of SNPs using Support Vector Machine. BMC Genetics. 11(1). 26–26. 64 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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