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
Highly diversified core promoters in the human genome and their effects on gene expression and disease predisposition.
Hemant Gupta,Khyati Chandratre,Siddharth Sinha,Teng Huang,Xiaobing Wu,Jian Cui,Michael Q. Zhang,San Ming Wang +7 more
TL;DR: Data from this study reals the highly diversified nature of core promoter in the human genome, and highlights that core promoter variation could play important roles not only in gene expression regulation but also in disease predisposition.
Journal ArticleDOI
Super-paramagnetic clustering of yeast gene expression profiles
TL;DR: In this paper, a Super-Paramagnetic Clustering (SPC) algorithm was used to organize genes into biologically relevant clusters that are suggestive for their co-regulation and revealed interesting correlated behavior of several groups of genes which has not been previously identified.
Proceedings ArticleDOI
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
TL;DR: In this paper , a multi-rate VAE (MR-VAE) is proposed to learn a response function that maps the reconstruction error (distortion) and the KL divergence (rate) using hypernetworks.
Book ChapterDOI
Identification of Splicing Factor Target Genes by High-Throughput Sequencing
Chaolin Zhang,Michael Q. Zhang +1 more
Journal ArticleDOI
MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data with transition pathway and critical point detection.
Zhen-Yi Wang,Yanjie Zhong,Yanjie Zhong,Zhaofeng Ye,Lang Zeng,Yang Chen,Minglei Shi,Zhiyuan Yuan,Qiming Zhou,Min-Ping Qian,Michael Q. Zhang,Michael Q. Zhang +11 more
TL;DR: In this paper, the authors proposed a novel Markov hierarchical clustering algorithm (MarkovHC), a topological clustering method that leverages the metastability of exponentially perturbed Markov chains for systematically reconstructing the cellular landscape.