S
Samuel S. M. Sun
Researcher at The Chinese University of Hong Kong
Publications - 66
Citations - 3653
Samuel S. M. Sun is an academic researcher from The Chinese University of Hong Kong. The author has contributed to research in topics: Genetically modified rice & Lysine. The author has an hindex of 29, co-authored 66 publications receiving 3168 citations. Previous affiliations of Samuel S. M. Sun include Yangzhou University & Tsinghua University.
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Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection
Hon-Ming Lam,Xun Xu,Xin Liu,Wenbin Chen,Guohua Yang,Fuk-Ling Wong,Man-Wah Li,Weiming He,Nan Qin,Bo Wang,Jun Li,Min Jian,Jing Wang,Guihua Shao,Jun Wang,Samuel S. M. Sun,Gengyun Zhang +16 more
TL;DR: A high level of linkage disequilibrium in the soybean genome is identified, suggesting that marker-assisted breeding of soybean will be less challenging than map-based cloning and to facilitate future breeding and quantitative trait analysis.
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Food supply and food safety issues in China
TL;DR: Important factors limiting agricultural production in China are identified, including conversion of agricultural land to other uses, freshwater deficits, and soil quality issues, and increased demand for some agricultural products is examined, particularly those needed to satisfy the increased consumption of animal products in the Chinese diet.
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An Interaction Between BZR1 and DELLAs Mediates Direct Signaling Crosstalk Between Brassinosteroids and Gibberellins in Arabidopsis
TL;DR: The data indicated that BZR1 and RGA served as positive and negative regulators, respectively, of both the BR and the GA signaling pathways and establish DELLAs as mediators of signaling crosstalk between BRs and GAs in controlling cell elongation and regulation of plant growth.
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Plant seeds as bioreactors for recombinant protein production
On Sun Lau,Samuel S. M. Sun +1 more
TL;DR: Current progress on seeds as bioreactors is reviewed, with focus on the different food crops as production platforms and comprehensive strategies in optimizing recombinant protein production in seeds.
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Validation of Candidate Reference Genes for the Accurate Normalization of Real-Time Quantitative RT-PCR Data in Rice During Seed Development
TL;DR: This study showed that eIF-4a and ACT1 were the most suitable reference genes among almost all the tested samples from two rice varieties, including different temporal and spatial-specific tissues, especially in seeds at different developmental stages.