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Shiqi Tu
Researcher at Chinese Academy of Sciences
Publications - 16
Citations - 153
Shiqi Tu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Chemistry & Computer science. The author has an hindex of 4, co-authored 7 publications receiving 51 citations. Previous affiliations of Shiqi Tu include CAS-MPG Partner Institute for Computational Biology.
Papers
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Journal ArticleDOI
MAnorm2 for quantitatively comparing groups of ChIP-seq samples.
Shiqi Tu,Shiqi Tu,Mushan Li,Haojie Chen,Haojie Chen,Fengxiang Tan,Fengxiang Tan,Jian Xu,David J. Waxman,Yijing Zhang,Zhen Shao +10 more
TL;DR: It is observed that MAnorm2 clearly outperformed existing tools for differential ChIP-seq analysis, especially when the groups of samples being compared had distinct global within-group variability.
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An introduction to computational tools for differential binding analysis with ChIP-seq data
TL;DR: The methods are extensively classified by their strategy of statistical modeling and scope of application, and a decision tree is presented for choosing proper tools based on the specific dataset.
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Nanomedicine Strategies for Heating “Cold” Ovarian Cancer (OC): Next Evolution in Immunotherapy of OC
Yuqi Yang,Tianjiao Zhao,Qiaohui Chen,Yu-meng Li,Zuoxiu Xiao,Yu Xiang,Boyu Wang,Yige Qiu,Shiqi Tu,Yitian Jiang,Yayun Nan,Qiong Huang,Kelong Ai +12 more
TL;DR: Current nanomedicines are comprehensively summarized through five general strategies to substantially enhance the efficacy of immunotherapy by heating the cold OC, and the challenges and perspectives of this expanding field for improved development of clinical applications are discussed.
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The PRC2-binding long non-coding RNAs in human and mouse genomes are associated with predictive sequence features
TL;DR: This work took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features by developing a new computational pipeline for sequences composition analysis, which found PRC2-binding lnc RNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features.
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State of the Art Advancements in Sonodynamic Therapy (SDT): Metal-Organic Frameworks for SDT
Zuoxiu Xiao,Qiaohui Chen,Yuqi Yang,Shiqi Tu,Boyu Wang,Yige Qiu,Yitian Jiang,Qiong Huang,Kelong Ai +8 more
TL;DR: In this paper , a review of metal organic frameworks (MOFs) based sonodynamic therapy (SDT) is provided, and various solutions adopted by MOFs to overcome the problems of SDT, including super-efficient sonosensitizer carriers, metal ion-optimized MOFs, multifunctional platforms for synergistic therapy, and MOFs as templates to prepare efficient nano-sonosensizers.