Eunmi Lee

1.1k total citations
42 papers, 759 citations indexed

About

Eunmi Lee is a scholar working on Molecular Biology, Electrical and Electronic Engineering and Oncology. According to data from OpenAlex, Eunmi Lee has authored 42 papers receiving a total of 759 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Electrical and Electronic Engineering and 6 papers in Oncology. Recurrent topics in Eunmi Lee's work include Advancements in Photolithography Techniques (4 papers), Streptococcal Infections and Treatments (3 papers) and Neonatal and Maternal Infections (3 papers). Eunmi Lee is often cited by papers focused on Advancements in Photolithography Techniques (4 papers), Streptococcal Infections and Treatments (3 papers) and Neonatal and Maternal Infections (3 papers). Eunmi Lee collaborates with scholars based in South Korea, United States and Italy. Eunmi Lee's co-authors include Do-Sik Shim, Raziye Piranlioglu, John K. Cowell, Daniela Marasco, Maria Ouzounova, Hasan Körkaya, Ahmed Chadli, Khaled A. Hassan, Ravindra Kolhe and Gang Zhou and has published in prestigious journals such as Nature Communications, Oncogene and Materials Science and Engineering A.

In The Last Decade

Eunmi Lee

36 papers receiving 745 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eunmi Lee South Korea	12	221	182	169	125	87	42	759
Wei Teng Taiwan	18	109 0.5×	95 0.5×	194 1.1×	314 2.5×	108 1.2×	85	1.0k
Yu Yao China	12	505 2.3×	81 0.4×	206 1.2×	131 1.0×	19 0.2×	39	1.1k
Weidong Zhao China	18	97 0.4×	141 0.8×	443 2.6×	157 1.3×	15 0.2×	61	1.2k
Xiangning Wang China	14	112 0.5×	448 2.5×	231 1.4×	189 1.5×	9 0.1×	58	1.4k
Michael Erdmann Germany	16	322 1.5×	487 2.7×	256 1.5×	95 0.8×	31 0.4×	67	1.0k
Hiroyuki Kobayashi Japan	17	71 0.3×	87 0.5×	138 0.8×	113 0.9×	20 0.2×	95	1.0k
Chengyue Wang China	14	53 0.2×	53 0.3×	159 0.9×	53 0.4×	121 1.4×	47	599
Qian Yuan China	16	394 1.8×	115 0.6×	382 2.3×	35 0.3×	18 0.2×	40	959
Peng Peng China	22	282 1.3×	195 1.1×	793 4.7×	73 0.6×	24 0.3×	78	1.5k

Countries citing papers authored by Eunmi Lee

Since Specialization

Citations

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

Fields of papers citing papers by Eunmi Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eunmi Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Eunmi Lee. A scholar is included among the top collaborators of Eunmi Lee 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 Eunmi Lee. Eunmi Lee 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

Lee, Dong‐Hyeon, Eunmi Lee, Junghwan Cho, et al.. (2024). Transcriptomic analysis reveals Streptococcus agalactiae activation of oncogenic pathways in cervical adenocarcinoma. Oncology Letters. 28(6). 588–588.

Lee, Eunmi, et al.. (2024). The Mclust Analysis of Tumor Budding Unveils the Role of the Collagen Family in Cervical Cancer Progression. Life. 14(8). 1004–1004. 2 indexed citations

Lee, Eunmi, Dong Hyeon Lee, Junghwan Cho, et al.. (2023). Relationship between Human Papillomavirus Status and the Cervicovaginal Microbiome in Cervical Cancer. Microorganisms. 11(6). 1417–1417. 16 indexed citations

Lee, Dong Hyeon, Eunmi Lee, Gun Oh Chong, et al.. (2023). Relationship between maternal Group B Streptococcal colonization and gestational vaginal microbiome composition: A pilot study. Indian Journal of Medical Microbiology. 46. 100426–100426. 3 indexed citations

Lee, Dong Hyeon, Eunmi Lee, Junghwan Cho, et al.. (2023). Profiling of Lymphovascular Space Invasion in Cervical Cancer Revealed PI3K/Akt Signaling Pathway Overactivation and Heterogenic Tumor-Immune Microenvironments. Life. 13(12). 2342–2342. 2 indexed citations

Han, Hyung Soo, Eunmi Lee, Dong‐Hyeon Lee, et al.. (2022). Simple Electric Device to Isolate Nucleic Acids from Whole BloodOptimized for Point of Care Testing of Brain Damage. Current Neurovascular Research. 19(3). 333–343. 1 indexed citations

Park, Ji Young, Eunmi Lee, Dong Hyeon Lee, et al.. (2022). Immune Pathway and Gene Database (IMPAGT) Revealed the Immune Dysregulation Dynamics and Overactivation of the PI3K/Akt Pathway in Tumor Buddings of Cervical Cancer. Current Issues in Molecular Biology. 44(11). 5139–5152. 8 indexed citations

Karki, Manohar, Junghwan Cho, Eunmi Lee, et al.. (2020). CT window trainable neural network for improving intracranial hemorrhage detection by combining multiple settings. Artificial Intelligence in Medicine. 106. 101850–101850. 31 indexed citations

Cho, Junghwan, Ki‐Su Park, Manohar Karki, et al.. (2019). Improving Sensitivity on Identification and Delineation of Intracranial Hemorrhage Lesion Using Cascaded Deep Learning Models. Journal of Digital Imaging. 32(3). 450–461. 93 indexed citations

10.

Lee, Eunmi, Maria Ouzounova, Raziye Piranlioglu, et al.. (2018). The pleiotropic effects of TNFα in breast cancer subtypes is regulated by TNFAIP3/A20. Oncogene. 38(4). 469–482. 30 indexed citations

11.

Kim, Ah-Young, Eunmi Lee, Eunjoo H. Lee, et al.. (2018). SIRT2 is required for efficient reprogramming of mouse embryonic fibroblasts toward pluripotency. Cell Death and Disease. 9(9). 893–893. 9 indexed citations

12.

Ouzounova, Maria, Eunmi Lee, Raziye Piranlioglu, et al.. (2017). Monocytic and granulocytic myeloid derived suppressor cells differentially regulate spatiotemporal tumour plasticity during metastatic cascade. Nature Communications. 8(1). 14979–14979. 287 indexed citations

13.

Lee, Eunmi & Kanghee Lee. (2016). Proposal of Class Scenario Design Method for Robot-aided Class. Advanced science and technology letters. 143–145.

14.

Lee, Eunmi, Ah-Young Kim, Eun‐Joo Lee, et al.. (2016). Splenic angiomyxoma with intravascular tumor embolus in a dog: a case report. Journal of Veterinary Medical Science. 78(6). 1085–1088. 1 indexed citations

15.

Lee, Eunmi & Kanghee Lee. (2014). An Implementation of Artificial Docent to Recommend Abstract Art. Journal of Basic Design & Art. 15(4). 413–421. 1 indexed citations

16.

Lee, Eunmi, et al.. (2012). A study on place storytelling using local folktales. 10(2). 315–316.

17.

Yang, Hai, Eunmi Lee, Ah-Young Kim, et al.. (2011). Angiotropic metastatic malignant melanoma in a canine mammary gland. Laboratory Animal Research. 27(4). 353–353. 1 indexed citations

18.

Ki, Mi‐Ran, Jin‐Kyu Park, Il‐Hwa Hong, et al.. (2010). Helicobacter pylori accelerates hepatic fibrosis by sensitizing transforming growth factor-β1-induced inflammatory signaling. Laboratory Investigation. 90(10). 1507–1516. 46 indexed citations

19.

Lee, Eunmi, et al.. (2009). Test and performance comparison of end-to-end available bandwidth measurement tools. 1. 370–372. 3 indexed citations

20.

Kim, Young-Chan & Eunmi Lee. (2007). The Estimation of Link Travel Time for Oversaturated Intersections from COSMOS Detector Data. 27. 189–198. 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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