Fang‐Yu Lin

1.1k total citations
39 papers, 816 citations indexed

About

Fang‐Yu Lin is a scholar working on Public Health, Environmental and Occupational Health, Oncology and Molecular Biology. According to data from OpenAlex, Fang‐Yu Lin has authored 39 papers receiving a total of 816 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Public Health, Environmental and Occupational Health, 9 papers in Oncology and 7 papers in Molecular Biology. Recurrent topics in Fang‐Yu Lin's work include Nutritional Studies and Diet (14 papers), Cancer Risks and Factors (7 papers) and Folate and B Vitamins Research (5 papers). Fang‐Yu Lin is often cited by papers focused on Nutritional Studies and Diet (14 papers), Cancer Risks and Factors (7 papers) and Folate and B Vitamins Research (5 papers). Fang‐Yu Lin collaborates with scholars based in China, United States and Hong Kong. Fang‐Yu Lin's co-authors include Cai‐Xia Zhang, Suzanne C. Ho, Yu‐Ming Chen, Jianhua Fu, Shouzhen Cheng, Xiong‐Fei Mo, Ching‐Hsing Wang, Jing Huang, Wuqing Huang and Naiqi Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Cancer.

In The Last Decade

Fang‐Yu Lin

37 papers receiving 789 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Fang‐Yu Lin 288 212 154 111 105 39 816
Katarzyna E. Przybyłowicz 260 0.9× 265 1.3× 263 1.7× 60 0.5× 202 1.9× 46 1.2k
Ritva R. Butrum 188 0.7× 99 0.5× 140 0.9× 106 1.0× 129 1.2× 24 661
Archana J. McEligot 206 0.7× 217 1.0× 193 1.3× 63 0.6× 113 1.1× 37 845
L Bergkvist 189 0.7× 194 0.9× 99 0.6× 81 0.7× 98 0.9× 9 616
RA Goldbohm 279 1.0× 92 0.4× 196 1.3× 82 0.7× 85 0.8× 5 831
Torukiri I Ibiebele 581 2.0× 374 1.8× 284 1.8× 110 1.0× 284 2.7× 55 1.7k
Hongmei Wu 225 0.8× 161 0.8× 257 1.7× 50 0.5× 254 2.4× 73 1.2k
Raphaëlle L. Santarelli 328 1.1× 128 0.6× 214 1.4× 74 0.7× 147 1.4× 7 773
Demetrius Albanes 238 0.8× 231 1.1× 145 0.9× 117 1.1× 148 1.4× 26 1.0k
Rikke Egeberg 407 1.4× 165 0.8× 83 0.5× 86 0.8× 207 2.0× 14 666

Countries citing papers authored by Fang‐Yu Lin

Since Specialization
Citations

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

Fields of papers citing papers by Fang‐Yu Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang‐Yu Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Fang‐Yu Lin. A scholar is included among the top collaborators of Fang‐Yu 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 Fang‐Yu Lin. Fang‐Yu 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, Fang‐Yu, Ying Li, Rebecca King, et al.. (2024). POU6F2, a risk factor for glaucoma, myopia and dyslexia, labels specific populations of retinal ganglion cells. Scientific Reports. 14(1). 10096–10096. 1 indexed citations
2.
Lin, Fang‐Yu, et al.. (2024). Optimizing retinal ganglion cell nuclear staining for automated cell counting. Experimental Eye Research. 242. 109881–109881. 1 indexed citations
3.
Li, Ru, et al.. (2023). Lung Nodule Segmentation Algorithm With SMR-UNet. IEEE Access. 11. 34319–34331. 16 indexed citations
4.
Liang, Lu, Wenyan Xu, Siran Wang, et al.. (2023). Inhibition of YAP1 activity ameliorates acute lung injury through promotion of M2 macrophage polarization. SHILAP Revista de lepidopterología. 4(3). e293–e293. 17 indexed citations
5.
Lin, Fang‐Yu, et al.. (2023). DMC-UNet-Based Segmentation of Lung Nodules. IEEE Access. 11. 110809–110826. 4 indexed citations
6.
Lin, Yu‐Chuan, Chun‐Hung Hua, Shi‐Wei Huang, et al.. (2023). CAR-T cells targeting HLA-G as potent therapeutic strategy for EGFR-mutated and overexpressed oral cancer. iScience. 26(3). 106089–106089. 6 indexed citations
7.
Zhu, Jing, et al.. (2022). Exploring the effect of perceived overqualification on knowledge hiding: The role of psychological capital and person-organization fit. Frontiers in Psychology. 13. 955661–955661. 9 indexed citations
8.
Kiong, Kimberley L., Christopher M. K. L. Yao, Fang‐Yu Lin, et al.. (2021). Delay to surgery after neoadjuvant chemotherapy in head and neck squamous cell carcinoma affects oncologic outcomes. Cancer. 127(12). 1984–1992. 4 indexed citations
9.
Liu, Kai‐Yan, Xiaoli Feng, Xiong‐Fei Mo, et al.. (2021). Iron intake with the risk of breast cancer among Chinese women: a case–control study. Public Health Nutrition. 24(17). 5743–5755. 5 indexed citations
10.
Kiong, Kimberley L., Fang‐Yu Lin, Christopher M. K. L. Yao, et al.. (2020). Impact of neoadjuvant chemotherapy on perioperative morbidity after major surgery for head and neck cancer. Cancer. 126(19). 4304–4314. 9 indexed citations
11.
Zhang, Naiqi, Xiong‐Fei Mo, Fang‐Yu Lin, et al.. (2020). Intake of total cruciferous vegetable and its contents of glucosinolates and isothiocyanates, glutathione S-transferases polymorphisms and breast cancer risk: a case–control study in China. British Journal Of Nutrition. 124(6). 548–557. 4 indexed citations
12.
Huang, Wuqing, Weiqing Long, Xiong‐Fei Mo, et al.. (2019). Direct and indirect associations between dietary magnesium intake and breast cancer risk. Scientific Reports. 9(1). 5764–5764. 27 indexed citations
13.
Zhang, Naiqi, Suzanne C. Ho, Xiong‐Fei Mo, et al.. (2018). Glucosinolate and isothiocyanate intakes are inversely associated with breast cancer risk: a case–control study in China. British Journal Of Nutrition. 119(8). 957–964. 33 indexed citations
14.
Huang, Wuqing, Xiong‐Fei Mo, Yanbin Ye, et al.. (2017). A higher Dietary Inflammatory Index score is associated with a higher risk of breast cancer among Chinese women: a case–control study. British Journal Of Nutrition. 117(10). 1358–1367. 36 indexed citations
15.
Lin, Fang‐Yu & Shyh‐Jen Wang. (2013). Identification of the factors that result in obviousness rulings for biotech patents. Human Vaccines & Immunotherapeutics. 9(11). 2490–2495. 4 indexed citations
16.
Zhang, Cai‐Xia, et al.. (2011). Dietary folate, vitamin B6, vitamin B12 and methionine intake and the risk of breast cancer by oestrogen and progesterone receptor status. British Journal Of Nutrition. 106(6). 936–943. 35 indexed citations
17.
Zhang, Cai‐Xia, et al.. (2011). Dietary fat intake and risk of breast cancer. European Journal of Cancer Prevention. 20(3). 199–206. 12 indexed citations
18.
Zhang, Cai‐Xia, Suzanne C. Ho, Fang‐Yu Lin, et al.. (2009). Soy product and isoflavone intake and breast cancer risk defined by hormone receptor status. Cancer Science. 101(2). 501–507. 51 indexed citations
19.
Zhang, Cai‐Xia, et al.. (2009). Meat and egg consumption and risk of breast cancer among Chinese women. Cancer Causes & Control. 20(10). 1845–1853. 31 indexed citations
20.
Zhang, Cai‐Xia, Suzanne C. Ho, Yu‐Ming Chen, et al.. (2009). Greater vegetable and fruit intake is associated with a lower risk of breast cancer among Chinese women. International Journal of Cancer. 125(1). 181–188. 163 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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