Eugene Lin

3.0k total citations
85 papers, 2.1k citations indexed

About

Eugene Lin is a scholar working on Molecular Biology, Genetics and Physiology. According to data from OpenAlex, Eugene Lin has authored 85 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 27 papers in Genetics and 11 papers in Physiology. Recurrent topics in Eugene Lin's work include Genetic Associations and Epidemiology (20 papers), Bioinformatics and Genomic Networks (13 papers) and Diet and metabolism studies (7 papers). Eugene Lin is often cited by papers focused on Genetic Associations and Epidemiology (20 papers), Bioinformatics and Genomic Networks (13 papers) and Diet and metabolism studies (7 papers). Eugene Lin collaborates with scholars based in Taiwan, United States and United Kingdom. Eugene Lin's co-authors include Shih‐Jen Tsai, Hsien‐Yuan Lane, Chieh‐Hsin Lin, Albert C. Yang, Po‐Hsiu Kuo, Hsien‐Yuan Lane, Tun-Jen Hsiao, Yu‐Li Liu, Yu-Li Liu and Po See Chen and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and PLoS ONE.

In The Last Decade

Eugene Lin

84 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eugene Lin Taiwan 28 734 387 214 213 212 85 2.1k
Xiangning Chen United States 28 955 1.3× 489 1.3× 94 0.4× 310 1.5× 203 1.0× 100 2.3k
Anbupalam Thalamuthu Australia 27 1000 1.4× 348 0.9× 96 0.4× 294 1.4× 92 0.4× 92 2.5k
Per Lindström Sweden 28 798 1.1× 458 1.2× 280 1.3× 601 2.8× 173 0.8× 111 3.4k
Chieh‐Hsin Lin Taiwan 31 875 1.2× 142 0.4× 149 0.7× 678 3.2× 118 0.6× 103 3.0k
David B. Keator United States 27 522 0.7× 200 0.5× 272 1.3× 386 1.8× 146 0.7× 89 2.5k
Antonella Santuccione Chadha Switzerland 17 714 1.0× 112 0.3× 57 0.3× 658 3.1× 114 0.5× 37 2.4k
Yu‐Li Liu Taiwan 26 613 0.8× 333 0.9× 73 0.3× 178 0.8× 25 0.1× 103 1.9k
Weihua Yue China 29 1.1k 1.5× 818 2.1× 195 0.9× 297 1.4× 72 0.3× 200 3.1k
Hongbao Cao United States 26 594 0.8× 423 1.1× 137 0.6× 183 0.9× 67 0.3× 138 2.0k
Alessio Squassina Italy 28 605 0.8× 479 1.2× 84 0.4× 270 1.3× 27 0.1× 105 2.0k

Countries citing papers authored by Eugene Lin

Since Specialization
Citations

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

Fields of papers citing papers by Eugene Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eugene Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Eugene Lin. A scholar is included among the top collaborators of Eugene Lin 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 Eugene Lin. Eugene Lin 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.
Lin, Eugene, Yu-Ting Yan, Mu‐Hong Chen, et al.. (2025). Gene clusters linked to insulin resistance identified in a genome-wide study of the Taiwan Biobank population. Nature Communications. 16(1). 3525–3525. 2 indexed citations
2.
Lin, Eugene, Po‐Hsiu Kuo, Wan‐Yu Lin, et al.. (2021). Prediction of Probable Major Depressive Disorder in the Taiwan Biobank: An Integrated Machine Learning and Genome-Wide Analysis Approach. Journal of Personalized Medicine. 11(7). 597–597. 8 indexed citations
3.
Lin, Eugene, Shih‐Jen Tsai, Po‐Hsiu Kuo, et al.. (2021). Genome-wide association study in the Taiwan Biobank identifies four novel genes for human height:NABP2, RASA2, RNF41andSLC39A5. Human Molecular Genetics. 30(23). 2362–2369. 8 indexed citations
4.
Tsai, Shih‐Jen, Po‐Hsiu Kuo, Yu‐Li Liu, et al.. (2020). An association study in the Taiwan Biobank reveals RORA as a novel locus for sleep duration in the Taiwanese Population. Sleep Medicine. 73. 70–75. 16 indexed citations
5.
Lin, Eugene, Po‐Hsiu Kuo, Yu‐Li Liu, et al.. (2020). Prediction of Antidepressant Treatment Response and Remission Using an Ensemble Machine Learning Framework. Pharmaceuticals. 13(10). 305–305. 31 indexed citations
6.
Lin, Eugene, Chieh‐Hsin Lin, & Hsien‐Yuan Lane. (2020). Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches. International Journal of Molecular Sciences. 21(3). 969–969. 92 indexed citations
7.
Lin, Eugene, Sudipto Mukherjee, & Sreeram Kannan. (2020). A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis. BMC Bioinformatics. 21(1). 64–64. 59 indexed citations
8.
Lin, Eugene, Po‐Hsiu Kuo, Yu‐Li Liu, Albert C. Yang, & Shih‐Jen Tsai. (2019). Polymorphisms of the DNA repair gene EXO1 modulate cognitive aging in old adults in a Taiwanese population. DNA repair. 78. 1–6. 12 indexed citations
9.
Liu, Yu-Li, Younger W.‐Y. Yu, Albert C. Yang, et al.. (2018). Gene-based analysis of genes related to neurotrophic pathway suggests association of BDNF and VEGFA with antidepressant treatment-response in depressed patients. Scientific Reports. 8(1). 6983–6983. 25 indexed citations
10.
Lin, Eugene, et al.. (2018). Combination of G72 Genetic Variation and G72 Protein Level to Detect Schizophrenia: Machine Learning Approaches. Frontiers in Psychiatry. 9. 566–566. 29 indexed citations
11.
Lin, Chieh‐Hsin, Eugene Lin, & Hsien‐Yuan Lane. (2017). Genetic Biomarkers on Age-Related Cognitive Decline. Frontiers in Psychiatry. 8. 247–247. 29 indexed citations
12.
Lin, Eugene, Albert C. Yang, & Shih‐Jen Tsai. (2017). Association between Metabolic Syndrome and Cognitive Function in Old Adults in a Taiwanese Population. 31(3). 7 indexed citations
13.
Lin, Eugene & Shih‐Jen Tsai. (2015). Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 64. 334–340. 42 indexed citations
14.
15.
Lane, Hsien‐Yuan, Guochuan Tsai, & Eugene Lin. (2012). Assessing Gene-Gene Interactions in Pharmacogenomics. Molecular Diagnosis & Therapy. 16(1). 15–27. 50 indexed citations
16.
Lin, Eugene, Dee Pei, Yi-Jen Huang, Chang‐Hsun Hsieh, & Lawrence Shih‐Hsin Wu. (2009). Gene-Gene Interactions Among Genetic Variants from Obesity Candidate Genes for Nonobese and Obese Populations in Type 2 Diabetes. Genetic Testing and Molecular Biomarkers. 13(4). 485–493. 31 indexed citations
17.
Lin, Eugene, Po See Chen, Hui Hua Chang, et al.. (2009). Interaction of serotonin-related genes affects short-term antidepressant response in major depressive disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 33(7). 1167–1172. 57 indexed citations
18.
Lin, Eugene, et al.. (2009). A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data. Journal of Translational Medicine. 7(1). 81–81. 53 indexed citations
19.
Lin, Eugene & Po See Chen. (2008). Pharmacogenomics with Antidepressants in the STAR*D Study. Pharmacogenomics. 9(7). 935–946. 52 indexed citations
20.
Lin, Eugene, et al.. (2008). A Bayesian Approach to Gene–Gene and Gene–Environment Interactions in Chronic Fatigue Syndrome. Pharmacogenomics. 10(1). 35–42. 24 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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