J
Jun Liu
Researcher at Sun Yat-sen University
Publications - 1474
Citations - 92168
Jun Liu is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 100, co-authored 1165 publications receiving 73692 citations. Previous affiliations of Jun Liu include Shanghai Jiao Tong University & Genome Institute of Singapore.
Papers
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Ovarian tissue cryopreservation: therapeutic prospects and ethical reflections
TL;DR: In this article, ovarian tissue cryopreservation has spurred interest in the medical literature as well as in the lay press as a method for preservation and restoring fertility, considering the available data and current state of knowledge, they would like to caution against unwarranted enthusiasm of physicians and patients.
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Advanced non-invasive MRI of neuroplasticity in ischemic stroke: Techniques and applications.
TL;DR: The ultimate goal of this review is to equip readers with a fundamental understanding of advanced MR techniques and their corresponding clinical application for improving the ability to predict neuroplasticity that are most suitable for stroke management.
Posted Content
Randomization Inference for Peer Effects
TL;DR: In this paper, a randomization-based inference framework is proposed to study peer effects with arbitrary numbers of peers and peer types, and the inferential procedure does not assume any parametric model on the outcome distribution.
Posted Content
Power of FDR Control Methods: The Impact of Ranking Algorithm, Tampered Design, and Symmetric Statistic
Zheng Tracy Ke,Jun Liu,Yucong Ma +2 more
TL;DR: The Rare/Weak signal model is adopted, popular in multiple testing and variable selection literature, and the rate of convergence of the number of false positives and the numberof false negatives of FDR control methods for particular classes of designs is characterized.
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Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly.
Jialiang Kuang,Jialiang Kuang,Marc W. Cadotte,Marc W. Cadotte,Yongjian Chen,Hao-Yue Shu,Jun Liu,Lin-Xing Chen,Zheng-Shuang Hua,Wen-Sheng Shu,Jizhong Zhou,Jizhong Zhou,Jizhong Zhou,Li-Nan Huang +13 more
TL;DR: The network-based analyses with three paralleled data sets derived from 16S rRNA gene pyrosequencing, functional microarray, and predicted metagenome suggest that deterministic trait-based community assembly results in greater conservation of network interaction, which may ensure ecosystem function across environmental regimes.