Shea Ping Yip

5.7k total citations
129 papers, 3.3k citations indexed

About

Shea Ping Yip is a scholar working on Molecular Biology, Epidemiology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shea Ping Yip has authored 129 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 32 papers in Epidemiology and 19 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shea Ping Yip's work include Ophthalmology and Visual Impairment Studies (18 papers), Corneal surgery and disorders (16 papers) and Retinal Diseases and Treatments (11 papers). Shea Ping Yip is often cited by papers focused on Ophthalmology and Visual Impairment Studies (18 papers), Corneal surgery and disorders (16 papers) and Retinal Diseases and Treatments (11 papers). Shea Ping Yip collaborates with scholars based in Hong Kong, China and United States. Shea Ping Yip's co-authors include Maurice Yap, Raymond Kai‐Yu Tong, Benjamin Yat‐Ming Yung, Lawrence Chan, Zheng Ke, Parco M. Siu, Sze Chuen Cesar Wong, Le Li, Thomas M. H. Lee and Xiaoxiang Zheng and has published in prestigious journals such as Nature Genetics, Blood and PLoS ONE.

In The Last Decade

Shea Ping Yip

125 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shea Ping Yip Hong Kong 32 914 662 430 418 415 129 3.3k
Danielle Seilhean France 44 1.8k 2.0× 696 1.1× 332 0.8× 591 1.4× 1.1k 2.5× 159 6.6k
Marcela Pekna Sweden 42 2.9k 3.1× 515 0.8× 313 0.7× 358 0.9× 1.2k 2.8× 97 8.6k
Jim Manavis Australia 33 1.0k 1.1× 734 1.1× 250 0.6× 442 1.1× 464 1.1× 134 4.0k
Takamichi Hattori Japan 53 870 1.0× 854 1.3× 617 1.4× 547 1.3× 1.0k 2.5× 308 8.6k
Francesco Tomasello Italy 43 766 0.8× 1.4k 2.1× 535 1.2× 733 1.8× 276 0.7× 243 5.9k
Douglas A. Kerr United States 43 1.6k 1.8× 361 0.5× 248 0.6× 1.4k 3.3× 331 0.8× 102 5.0k
Simon Yona Israel 41 3.3k 3.6× 903 1.4× 163 0.4× 301 0.7× 817 2.0× 74 10.6k
Richard M. McCarron United States 46 1.4k 1.5× 1.6k 2.4× 248 0.6× 293 0.7× 1.1k 2.6× 195 6.5k
Pamela McCombe Australia 45 1.3k 1.4× 392 0.6× 316 0.7× 922 2.2× 634 1.5× 231 6.5k
Harald Prüß Germany 46 1.3k 1.4× 756 1.1× 379 0.9× 779 1.9× 251 0.6× 222 7.0k

Countries citing papers authored by Shea Ping Yip

Since Specialization
Citations

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

Fields of papers citing papers by Shea Ping Yip

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shea Ping Yip. 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 Shea Ping Yip. The network helps show where Shea Ping Yip may publish in the future.

Co-authorship network of co-authors of Shea Ping Yip

This figure shows the co-authorship network connecting the top 25 collaborators of Shea Ping Yip. A scholar is included among the top collaborators of Shea Ping Yip 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 Shea Ping Yip. Shea Ping Yip 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.
Gedefaw, Lealem, et al.. (2023). Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders. Cells. 12(13). 1755–1755. 33 indexed citations
2.
Shan, Sze Wan, Feng Yu, Hui Zheng, et al.. (2022). Transcriptional profiling of the chick retina identifies down-regulation of VIP and UTS2B genes during early lens-induced myopia. Molecular Omics. 18(5). 449–459. 3 indexed citations
3.
Li, Wan‐Chun, et al.. (2020). Vascular Tissue Engineering: Advanced Techniques and Gene Editing in Stem Cells for Graft Generation. Tissue Engineering Part B Reviews. 27(1). 14–28. 23 indexed citations
4.
Yip, Shea Ping, et al.. (2017). Region-specific differential corneal and scleral mRNA expressions of MMP2, TIMP2, and TGFB2 in highly myopic-astigmatic chicks. Scientific Reports. 7(1). 11423–11423. 10 indexed citations
5.
Kao, Patrick Y.P., Kim Hung Leung, Lawrence Chan, Shea Ping Yip, & Maurice Yap. (2017). Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions General subjects. Biochimica et Biophysica Acta.
6.
Liao, Xuan, et al.. (2017). Genetic Association Study of KCNQ5 Polymorphisms with High Myopia. BioMed Research International. 2017. 1–7. 17 indexed citations
7.
Wang, Fengfeng, Lawrence Chan, Nancy B. Y. Tsui, et al.. (2015). Coexpression Pattern Analysis of NPM1-Associated Genes in Chronic Myelogenous Leukemia. BioMed Research International. 2015. 1–9. 6 indexed citations
8.
Yuan, Chuang, V. Wu, Shea Ping Yip, Dora L.�W. Kwong, & Michael Ying. (2014). Predictors of the Extent of Carotid Atherosclerosis in Patients Treated with Radiotherapy for Nasopharyngeal Carcinoma. PLoS ONE. 9(12). e116284–e116284. 13 indexed citations
9.
Kee, Chea‐su, et al.. (2013). Regional variations in corneal and scleral mRNA expressions of MMP2, TIMP2, TGFβ2 in highly myopic-astigmatic chicks. Investigative Ophthalmology & Visual Science. 54(15). 3676–3676.
10.
Pang, Marco Y.C., Ricky W.K. Lau, & Shea Ping Yip. (2013). The effects of whole-body vibration therapy on bone turnover, muscle strength, motor function, and spasticity in chronic stroke: a randomized controlled trial.. PubMed. 49(4). 439–50. 68 indexed citations
12.
Yip, Shea Ping, et al.. (2011). A DNA pooling-based case-control study of myopia candidate genes COL11A1, COL18A1, FBN1, and PLOD1 in a Chinese population.. PubMed. 17. 810–21. 7 indexed citations
13.
Chan, Kelvin Y.K., Vera Chan, Ying Chi Ip, et al.. (2010). Association of a single nucleotide polymorphism in the CD209 (DC-SIGN) promoter with SARS severity.. PubMed. 16(5 Suppl 4). 37–42. 19 indexed citations
14.
Khoo, US, Kelvin Y.K. Chan, Vera Chan, et al.. (2009). Functional role of ICAM-3 polymorphism in genetic susceptibility to SARS infection.. PubMed. 15 Suppl 6. 26–9. 2 indexed citations
15.
Song, You‐Qiang, Kmc Cheung, Daniel Wai‐Hung Ho, et al.. (2008). Association of the Asporin D14 Allele with Lumbar-Disc Degeneration in Asians. The American Journal of Human Genetics. 82(3). 744–747. 94 indexed citations
16.
Tang, Wing Chun, et al.. (2007). Linkage and association of myocilin (MYOC) polymorphisms with high myopia in a Chinese population.. PubMed. 13. 534–44. 42 indexed citations
17.
Cheung, Kmc, Danny Chan, Jaro Karppinen, et al.. (2006). Association of the Taq I Allele in Vitamin D Receptor With Degenerative Disc Disease and Disc Bulge in a Chinese Population. Spine. 31(10). 1143–1148. 114 indexed citations
18.
Yip, Shea Ping, et al.. (2004). Rapid Detection of Common Southeast Asian ß-Thalassemia Mutations by Nonisotopic Multiplex PCR-SSCP Analysis. Genetic Testing. 8(2). 104–108. 1 indexed citations
19.
Tang, Wan‐Yee, et al.. (2004). Testing for association between COL2A1 and myopia susceptibility in Hong Kong Chinese population. Investigative Ophthalmology & Visual Science. 45(13). 3724–3724. 3 indexed citations
20.
Tsui, Wilson M. S., et al.. (2000). The C282Y mutation of the HFE gene is not found in Chinese haemochromatotic patients: multicentre retrospective study.. PubMed. 6(2). 153–8. 17 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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