M
Michael Q. Zhang
Researcher at Tsinghua University
Publications - 396
Citations - 46412
Michael Q. Zhang is an academic researcher from Tsinghua University. The author has contributed to research in topics: Gene & Chromatin. The author has an hindex of 93, co-authored 378 publications receiving 42008 citations. Previous affiliations of Michael Q. Zhang include Chinese Academy of Sciences & Peking Union Medical College Hospital.
Papers
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Journal ArticleDOI
Genome mapping by nonrandom anchoring: a discrete theoretical analysis.
Michael Q. Zhang,Thomas G. Marr +1 more
TL;DR: A theoretical model is proposed to explain the simulated data and the experimental data and it is shown that the nonrandom anchoring method is far superior to random anchoring.
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Computational identification of active enhancers in model organisms.
TL;DR: The current computational approaches for active enhancer prediction are surveyed and the future directions are discussed to discuss future directions.
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A novel epigenetic AML1‐ETO/THAP10/miR‐383 mini‐circuitry contributes to t(8;21) leukaemogenesis
Yonghui Li,Qiaoyang Ning,Qiaoyang Ning,Jinlong Shi,Yang Chen,Mengmeng Jiang,Li Gao,Wenrong Huang,Yu Jing,Sai Huang,Anqi Liu,Zhirui Hu,Dai-Hong Liu,Li-Li Wang,Clara Nervi,Yun Dai,Yun Dai,Michael Q. Zhang,Li Yu +18 more
TL;DR: An unexpected and important epigenetic mini‐circuit of AML1‐ETO/THAP10/miR‐383 in t(8;21) AML is revealed, in which epigenetic suppression of THAP10 predicts a poor clinical outcome and represents a novel therapeutic target.
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Integrative genomic analysis of gemcitabine resistance in pancreatic cancer by patient-derived xenograft models
Gang Yang,Wenfang Guan,Zhe Cao,Wenbo Guo,Guangbing Xiong,Fangyu Zhao,Mengyu Feng,Jiangdong Qiu,Yueze Liu,Michael Q. Zhang,Michael Q. Zhang,Lei You,Taiping Zhang,Yupei Zhao,Jin Gu +14 more
TL;DR: Wang et al. as mentioned in this paper explored the molecular features of gemcitabine resistance and identified candidate biomarkers and combinatorial targets for the treatment of pancreatic cancer (PC) using a comprehensive multi-omics analysis and functional experiment.
Journal ArticleDOI
Analysis of C. elegans muscle transcriptome using trans-splicing-based RNA tagging (SRT).
Xiaopeng Ma,Ge Zhan,Monica C. Sleumer,Siyu Chen,Weihong Liu,Michael Q. Zhang,Michael Q. Zhang,Xiao Liu +7 more
TL;DR: The splicing-based RNA tagging (SRT) method provides a convenient and robust tool to profile trans-spliced genes and identify novel transcripts in a tissue-specific manner, with a low false positive rate.