Jen‐Ai Lee

2.1k total citations
80 papers, 1.8k citations indexed

About

Jen‐Ai Lee is a scholar working on Clinical Biochemistry, Molecular Biology and Biochemistry. According to data from OpenAlex, Jen‐Ai Lee has authored 80 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Clinical Biochemistry, 18 papers in Molecular Biology and 18 papers in Biochemistry. Recurrent topics in Jen‐Ai Lee's work include Metabolism and Genetic Disorders (18 papers), Amino Acid Enzymes and Metabolism (17 papers) and Diet and metabolism studies (12 papers). Jen‐Ai Lee is often cited by papers focused on Metabolism and Genetic Disorders (18 papers), Amino Acid Enzymes and Metabolism (17 papers) and Diet and metabolism studies (12 papers). Jen‐Ai Lee collaborates with scholars based in Taiwan, Japan and United States. Jen‐Ai Lee's co-authors include Kazuhiro Imai, Hiroshi Homma, Takeshi Iwatsubo, Takeshi Fukushima, Tomofumi Santa, Shih‐Ming Chen, Ken Tashiro, Yoshiko Nagata, Kumiko Sakai and Hsiang‐Yin Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Jen‐Ai Lee

75 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jen‐Ai Lee Taiwan 24 829 652 589 269 233 80 1.8k
Rafał Głowacki Poland 29 990 1.2× 299 0.5× 683 1.2× 23 0.1× 211 0.9× 106 2.7k
Edward Bald Poland 31 928 1.1× 188 0.3× 579 1.0× 24 0.1× 176 0.8× 86 2.5k
Yong Yu United States 20 332 0.4× 155 0.2× 748 1.3× 47 0.2× 409 1.8× 40 2.2k
Denis C. Lehotay Canada 30 131 0.2× 353 0.5× 822 1.4× 67 0.2× 251 1.1× 84 2.1k
Krista Laine Finland 26 324 0.4× 52 0.1× 602 1.0× 310 1.2× 92 0.4× 44 2.1k
Mario Fontana Italy 23 275 0.3× 60 0.1× 479 0.8× 80 0.3× 324 1.4× 115 1.7k
Reinhard Berkels Germany 25 226 0.3× 110 0.2× 523 0.9× 172 0.6× 377 1.6× 46 2.2k
Osama Y. Al-Dirbashi Canada 23 98 0.1× 288 0.4× 483 0.8× 53 0.2× 131 0.6× 68 1.4k
Ina Nemet United States 28 88 0.1× 557 0.9× 1.3k 2.2× 139 0.5× 689 3.0× 59 2.5k
Alex Dyson United Kingdom 28 312 0.4× 86 0.1× 568 1.0× 207 0.8× 319 1.4× 62 2.4k

Countries citing papers authored by Jen‐Ai Lee

Since Specialization
Citations

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

Fields of papers citing papers by Jen‐Ai Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jen‐Ai Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Jen‐Ai Lee. A scholar is included among the top collaborators of Jen‐Ai 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 Jen‐Ai Lee. Jen‐Ai Lee 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
1.
2.
Lee, Meng‐Rui, et al.. (2022). Bisphosphonate Use Is Not Associated With Tuberculosis Risk Among Patients With Osteoporosis: A Nationwide Cohort Study. The Journal of Clinical Pharmacology. 62(11). 1412–1418. 1 indexed citations
3.
Chen, Chien‐Ming, et al.. (2021). Evaluation of the nephrotoxicity and safety of low-dose aristolochic acid, extending to the use of Xixin (Asurum), by determination of methylglyoxal and d-lactate. Journal of Ethnopharmacology. 272. 113945–113945. 3 indexed citations
4.
Lee, Ming‐Chia, Tzu‐Rong Peng, Chih‐Hsin Lee, et al.. (2021). Effects of various statins on depressive symptoms: A network meta-analysis. Journal of Affective Disorders. 293. 205–213. 10 indexed citations
5.
Lee, Jen‐Ai, et al.. (2020). Utilizing methylglyoxal and D-lactate in urine to evaluate saikosaponin C treatment in mice with accelerated nephrotoxic serum nephritis. PLoS ONE. 15(10). e0241053–e0241053. 2 indexed citations
6.
7.
Chen, Shih‐Ming, et al.. (2014). Increased renal semicarbazide-sensitive amine oxidase activity and methylglyoxal levels in aristolochic acid-induced nephrotoxicity. Life Sciences. 114(1). 4–11. 19 indexed citations
8.
Hsu, Yu‐Wen, Shu‐Chen Chien, Chi-Cheng Liang, et al.. (2013). Stromal Interaction Molecule 1 Polymorphisms are Associated with Coronary Artery Dilation but not with Aneurysm Formation in Patients with Kawasaki Disease. Journal of Experimental & Clinical Medicine. 5(2). 73–76. 2 indexed citations
9.
Lee, Jen‐Ai, et al.. (2013). Gentamicin caused renal injury deeply related to methylglyoxal and Nɛ-(carboxyethyl)lysine (CEL). Toxicology Letters. 219(1). 85–92. 16 indexed citations
10.
Wei, Da‐Hua, et al.. (2012). Concurrent improvement in biocompatibility and bioinertness of diamond‐like carbon films with nitrogen doping. Journal of Biomedical Materials Research Part A. 100A(11). 3151–3156. 25 indexed citations
11.
Lin, Mei-Hsiang, et al.. (2011). Determination of time-dependent accumulation of d-lactate in the streptozotocin-induced diabetic rat kidney by column-switching HPLC with fluorescence detection. Journal of Chromatography B. 879(29). 3214–3219. 23 indexed citations
12.
Lee, Jen‐Ai, et al.. (2011). Tobacco consumption is a reversible risk factor associated with reduced successful treatment outcomes of anti-tuberculosis therapy. International Journal of Infectious Diseases. 16(2). e130–e135. 18 indexed citations
13.
Fukushima, Takeshi, et al.. (2011). Enantioselective determination of 3-hydroxybutyrate in the tissues of normal and streptozotocin-induced diabetic rats of different ages. Journal of Chromatography B. 879(29). 3331–3336. 23 indexed citations
14.
Kong, Doo‐Sik, et al.. (2008). Hemifacial spasm: neurovascular compressive patterns and surgical significance. Acta Neurochirurgica. 150(3). 235–241. 60 indexed citations
15.
Hsiao, Fei‐Yuan, et al.. (2006). Survey of Medication Knowledge and Behaviors Among College Students in Taiwan. American Journal of Pharmaceutical Education. 70(2). 30–30. 5 indexed citations
16.
Chou, Yu‐Ching, et al.. (2005). Stereoselective effects of 3-hydroxybutyrate on glucose utilization of rat cardiomyocytes. Life Sciences. 78(12). 1385–1391. 38 indexed citations
17.
Lee, Jen‐Ai, et al.. (2000). -Aspartate in a Prolactin-Secreting Clonal Strain of Rat Pituitary Tumor Cells (GH3). Biochemical and Biophysical Research Communications. 276(3). 1143–1147. 50 indexed citations
18.
Sakai, Kumiko, Hiroshi Homma, Jen‐Ai Lee, et al.. (1998). Emergence of d-aspartic acid in the differentiating neurons of the rat central nervous system. Brain Research. 808(1). 65–71. 75 indexed citations
19.
Lee, Jen‐Ai, Hiroshi Homma, Kumiko Sakai, et al.. (1997). Immunohistochemical Localization of D-Aspartate in the Rat Pineal Gland. Biochemical and Biophysical Research Communications. 231(2). 505–508. 75 indexed citations
20.
Sakai, Kumiko, Hiroshi Homma, Jen‐Ai Lee, et al.. (1997). D-Aspartic Acid Localization during Postnatal Development of Rat Adrenal Gland. Biochemical and Biophysical Research Communications. 235(2). 433–436. 54 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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