Shan‐Shan Kuo

642 total citations
8 papers, 521 citations indexed

About

Shan‐Shan Kuo is a scholar working on Genetics, Molecular Biology and Surgery. According to data from OpenAlex, Shan‐Shan Kuo has authored 8 papers receiving a total of 521 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Genetics, 4 papers in Molecular Biology and 2 papers in Surgery. Recurrent topics in Shan‐Shan Kuo's work include Genetic Associations and Epidemiology (5 papers), RNA modifications and cancer (2 papers) and Lipid metabolism and disorders (2 papers). Shan‐Shan Kuo is often cited by papers focused on Genetic Associations and Epidemiology (5 papers), RNA modifications and cancer (2 papers) and Lipid metabolism and disorders (2 papers). Shan‐Shan Kuo collaborates with scholars based in Taiwan and United States. Shan‐Shan Kuo's co-authors include Lee‐Ming Chuang, Tien‐Jyun Chang, Yi‐Cheng Chang, Yi-Der Jiang, Pi‐Hua Liu, Kuan‐Ching Lee, Ken C. Chiu, Hung‐Yuan Li, Wei‐Jei Lee and Thomas Quertermous and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Diabetes.

In The Last Decade

Shan‐Shan Kuo

8 papers receiving 510 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shan‐Shan Kuo Taiwan	8	301	249	98	88	72	8	521
Charles S. Janipalli India	4	270 0.9×	169 0.7×	125 1.3×	85 1.0×	64 0.9×	4	474
Mounia Tannour‐Louet United States	10	253 0.8×	328 1.3×	67 0.7×	108 1.2×	46 0.6×	13	569
Lauren Gianniny United States	4	381 1.3×	274 1.1×	175 1.8×	200 2.3×	37 0.5×	4	598
C S Rose Denmark	11	190 0.6×	152 0.6×	83 0.8×	144 1.6×	97 1.3×	12	423
C.E. Flück Switzerland	12	258 0.9×	223 0.9×	183 1.9×	58 0.7×	12 0.2×	16	566
Victoria Ossowski United States	12	128 0.4×	305 1.2×	65 0.7×	86 1.0×	123 1.7×	14	572
Noël P. Burtt United States	5	202 0.7×	135 0.5×	74 0.8×	103 1.2×	28 0.4×	6	341
Pamela A. McCaskie Australia	10	75 0.2×	120 0.5×	60 0.6×	67 0.8×	48 0.7×	14	337
A. Fusco Italy	12	67 0.2×	341 1.4×	201 2.1×	139 1.6×	36 0.5×	17	567
Kelly L. Krass United States	9	204 0.7×	180 0.7×	123 1.3×	108 1.2×	38 0.5×	9	431

Countries citing papers authored by Shan‐Shan Kuo

Since Specialization

Citations

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

Fields of papers citing papers by Shan‐Shan Kuo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shan‐Shan Kuo. 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 Shan‐Shan Kuo. The network helps show where Shan‐Shan Kuo may publish in the future.

Co-authorship network of co-authors of Shan‐Shan Kuo

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

All Works

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8 of 8 papers shown

Chang, Tien‐Jyun, Yen‐Feng Chiu, Wayne Huey‐Herng Sheu, et al.. (2015). Genetic polymorphisms of PCSK2 are associated with glucose homeostasis and progression to type 2 diabetes in a Chinese population. Scientific Reports. 5(1). 14380–14380. 22 indexed citations

Chang, Yi‐Cheng, Pi‐Hua Liu, Yu‐Hsiang Yu, et al.. (2014). Validation of Type 2 Diabetes Risk Variants Identified by Genome-Wide Association Studies in Han Chinese Population: A Replication Study and Meta-Analysis. PLoS ONE. 9(4). e95045–e95045. 41 indexed citations

Chang, Yi‐Cheng, Ling‐Yin Chang, Tien‐Jyun Chang, et al.. (2009). The Associations of LPIN1 Gene Expression in Adipose Tissue With Metabolic Phenotypes in the Chinese Population. Obesity. 18(1). 7–12. 26 indexed citations

Liu, Pi‐Hua, Yi‐Cheng Chang, Yi-Der Jiang, et al.. (2009). Genetic Variants ofTCF7L2Are Associated with Insulin Resistance and Related Metabolic Phenotypes in Taiwanese Adolescents and Caucasian Young Adults. The Journal of Clinical Endocrinology & Metabolism. 94(9). 3575–3582. 48 indexed citations

Chang, Yi‐Cheng, Pi‐Hua Liu, Wei‐Jei Lee, et al.. (2008). Common Variation in the Fat Mass and Obesity-Associated (FTO) Gene Confers Risk of Obesity and Modulates BMI in the Chinese Population. Diabetes. 57(8). 2245–2252. 179 indexed citations

Chang, Yi‐Cheng, Tien‐Jyun Chang, Yi-Der Jiang, et al.. (2007). Association Study of the Genetic Polymorphisms of the Transcription Factor 7-Like 2 (TCF7L2) Gene and Type 2 Diabetes in the Chinese Population. Diabetes. 56(10). 2631–2637. 143 indexed citations

Yen, Chung‐Jen, et al.. (2005). Interaction of the G182C polymorphism in the APOA5 gene and fasting plasma glucose on plasma triglycerides in Type 2 diabetic subjects. Diabetic Medicine. 22(12). 1690–1695. 8 indexed citations

Yang, Wei‐Shiung, Low Tone Ho, Chih‐Tsueng He, et al.. (2003). Genetic epistasis of adiponectin and PPAR?2 genotypes in modulation of insulin sensitivity: a family-based association study. Diabetologia. 46(7). 977–983. 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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