Eun Gae Lee

831 total citations · 1 hit paper
6 papers, 638 citations indexed

About

Eun Gae Lee is a scholar working on Epidemiology, Infectious Diseases and Surgery. According to data from OpenAlex, Eun Gae Lee has authored 6 papers receiving a total of 638 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Epidemiology, 5 papers in Infectious Diseases and 3 papers in Surgery. Recurrent topics in Eun Gae Lee's work include Tuberculosis Research and Epidemiology (5 papers), Mycobacterium research and diagnosis (5 papers) and Infectious Diseases and Tuberculosis (2 papers). Eun Gae Lee is often cited by papers focused on Tuberculosis Research and Epidemiology (5 papers), Mycobacterium research and diagnosis (5 papers) and Infectious Diseases and Tuberculosis (2 papers). Eun Gae Lee collaborates with scholars based in South Korea, United States and Bahrain. Eun Gae Lee's co-authors include Laura E. Via, Clifton E. Barry, Seung Kyu Park, Shannon Sedberry Allen, Philana Ling Lin, Seok Yong Eum, Ujjini H. Manjunatha, JoAnne L. Flynn, Edwin Klein and José Carrillo and has published in prestigious journals such as Journal of Clinical Microbiology, Infection and Immunity and Veterinary Microbiology.

In The Last Decade

Eun Gae Lee

6 papers receiving 632 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Tuberculous Granulomas Are Hypoxic in Guinea Pigs, Rabbits, and Nonhuman Primates

2008 498 citations Laura E. Via, Philana Ling Lin et al. Infection and Immunity profile →

Peers

Eun Gae Lee

ID

EPIDE

SURGE

MB

MM

Krishnamoorthy Gopinath India

Sahar Aly Germany

Rachel L. Leistikow United States

Uma Shankar Gautam United States

Robert A. Reich United States

Davide Pisu United States

Ciaran Skerry United States

Ruiru Shi China

Emily Driver United States

Ashley M. Sherrid United States

Krishnamoorthy Gopinath India

Eun Gae Lee

528 ×1.0

ID

473 ×1.1

EPIDE

178 ×1.0

SURGE

213 ×1.2

MB

43 ×0.6

MM

Citations per year, relative to Eun Gae Lee Eun Gae Lee (= 1×) peers Krishnamoorthy Gopinath

Countries citing papers authored by Eun Gae Lee

Since Specialization

Citations

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

Fields of papers citing papers by Eun Gae Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eun Gae Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Eun Gae Lee. A scholar is included among the top collaborators of Eun Gae 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 Eun Gae Lee. Eun Gae 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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6 of 6 papers shown

1.

Chakravorty, Soumitesh, Eun Jin Cho, Jong Seok Lee, et al.. (2012). Rapid, High-Throughput Detection of Rifampin Resistance and Heteroresistance in Mycobacterium tuberculosis by Use of Sloppy Molecular Beacon Melting Temperature Coding. Journal of Clinical Microbiology. 50(7). 2194–2202. 29 indexed citations

2.

Shamputa, Isdore Chola, Jongseok Lee, Eun Gae Lee, et al.. (2010). Genetic diversity of Mycobacterium tuberculosis isolates from a tertiary care tuberculosis hospital in South Korea. 48(2). 387–394. 1 indexed citations

3.

Chakravorty, Soumitesh, Jong Seok Lee, Eun Gae Lee, et al.. (2010). Rapid Detection of Fluoroquinolone-Resistant and Heteroresistant Mycobacterium tuberculosis by Use of Sloppy Molecular Beacons and Dual Melting-Temperature Codes in a Real-Time PCR Assay. Journal of Clinical Microbiology. 49(3). 932–940. 40 indexed citations

4.

Shamputa, Isdore Chola, Jongseok Lee, Caroline Allix‐Béguec, et al.. (2009). Genetic Diversity of Mycobacterium tuberculosis Isolates from a Tertiary Care Tuberculosis Hospital in South Korea. Journal of Clinical Microbiology. 48(2). 387–394. 63 indexed citations

5.

Via, Laura E., Philana Ling Lin, José Carrillo, et al.. (2008). Tuberculous Granulomas Are Hypoxic in Guinea Pigs, Rabbits, and Nonhuman Primates. Infection and Immunity. 76(6). 2333–2340. 498 indexed citations breakdown →

6.

Seok, Seung Hyeok, Hye Cheong Koo, Yeun Kim, et al.. (2006). Use of PCR-restriction fragment length polymorphism for the identification of zoonotic mycobacteriosis in zebrafish caused by Mycobacterium abscessus and Mycobacterium chelonae. Veterinary Microbiology. 114(3-4). 292–297. 7 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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