Y
Yue Liu
Researcher at University of Minnesota
Publications - 22
Citations - 1882
Yue Liu is an academic researcher from University of Minnesota. The author has contributed to research in topics: Gene & Biology. The author has an hindex of 9, co-authored 15 publications receiving 1211 citations. Previous affiliations of Yue Liu include China Agricultural University & Qingdao Agricultural University.
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agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update.
TL;DR: The updated agriGO that has a largely expanded number of supporting species and datatypes and more visualization features were added to the platform, including SEACOMPARE, direct acyclic graph (DAG) and Scatter Plots, which can be merged by choosing any significant GO term.
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PCSD: a plant chromatin state database.
TL;DR: A PCSD database integrated the identified chromatin states with epigenetic features and may be beneficial for communities to discover causal functions hidden in plant chromatin.
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A tandem segmental duplication (TSD) in green revolution gene Rht-D1b region underlies plant height variation
Yiyuan Li,Jianhui Xiao,Jiajie Wu,Jialei Duan,Yue Liu,Xingguo Ye,Xin Zhang,Xiuping Guo,Yongqiang Gu,Lichao Zhang,Jizeng Jia,Xiuying Kong +11 more
TL;DR: The results suggest that changes in gene copy number are one of the important sources of genetic diversity and some of these changes could be directly associated with important traits in crops.
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A TRIM insertion in the promoter of Ms2 causes male sterility in wheat.
Chuan Xia,Lichao Zhang,Cheng Zou,Yongqiang Gu,Jialei Duan,Guangyao Zhao,Jiajie Wu,Yue Liu,Xiaohua Fang,Lifeng Gao,Yuannian Jiao,Jiaqiang Sun,Yinghong Pan,Xu Liu,Jizeng Jia,Xiuying Kong +15 more
TL;DR: The identification of Ms2 not only unravels the genetic basis of a historically important breeding trait, but also shows an example of how a TRIM element insertion near a gene can contribute to genetic novelty and phenotypic plasticity.
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AppleMDO: A Multi-Dimensional Omics Database for Apple Co-Expression Networks and Chromatin States.
TL;DR: Through integration of the available apple genomic, transcriptomic, and epigenomic datasets, co-expression networks, identified functional modules, and predicted chromatin states are constructed, which showed that the function of many modules was related to development, secondary metabolism, hormone response, and transcriptional regulation.