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Xiaotong Luo
Researcher at Sun Yat-sen University
Publications - 15
Citations - 1263
Xiaotong Luo is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: RNA & Medicine. The author has an hindex of 7, co-authored 12 publications receiving 746 citations.
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Journal ArticleDOI
IBS: an illustrator for the presentation and visualization of biological sequences.
Wenzhong Liu,Yubin Xie,Jiyong Ma,Xiaotong Luo,Peng Nie,Zhixiang Zuo,Urs Lahrmann,Qi Zhao,Yueyuan Zheng,Yong Zhao,Yu Xue,Jian Ren +11 more
TL;DR: A software package called illustrator of biological sequences (IBS) that can be used for representing the organization of either protein or nucleotide sequences in a convenient, efficient and precise manner.
Journal ArticleDOI
METTL3 and N6-Methyladenosine Promote Homologous Recombination-Mediated Repair of DSBs by Modulating DNA-RNA Hybrid Accumulation
Canfeng Zhang,Liping Chen,Di Peng,Ao Jiang,Yunru He,Yanru Zeng,Chen Xie,Haoxian Zhou,Xiaotong Luo,Haiying Liu,Liang Chen,Jian Ren,Wengong Wang,Yong Zhao +13 more
TL;DR: In this paper, the RNA methyltransferase METTL3 is activated by ATM-mediated phosphorylation at S43, where it methylates the N6 position of adenosine (m6A) in DNA damage-associated RNAs, which recruits the m6A reader protein YTHDC1 for protection.
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GPS-Lipid: a robust tool for the prediction of multiple lipid modification sites
Yubin Xie,Yueyuan Zheng,Hongyu Li,Xiaotong Luo,Zhihao He,Shuo Cao,Yi Shi,Qi Zhao,Qi Zhao,Yu Xue,Zhixiang Zuo,Jian Ren,Jian Ren +12 more
TL;DR: A systematic analysis of the co-regulatory mechanism between different lipid modifications with GPS-Lipid demonstrated that the proximal dual-lipid modifications among palmitoylation, myristoylation and prenylation are key mechanism for regulating various protein functions.
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RMVar: an updated database of functional variants involved in RNA modifications.
TL;DR: An updated version of m6AVar, developed to host all RNA modification (RM)-associated variants, is presented, renamed RMVar, and it is expected that RMVar may boost further functional studies on genetic variants affecting RNA modifications.
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DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning.
Yubin Xie,Xiaotong Luo,Yupeng Li,Li Chen,Wenbin Ma,Junjiu Huang,Jun Cui,Yong Zhao,Yu Xue,Zhixiang Zuo,Jian Ren +10 more
TL;DR: The application of deep learning method and novel encoding schemes, especially the position-specific scoring feature, greatly improves the accuracy of nitration and nitrosylation site prediction and may facilitate the prediction of other PTM sites.