2006 - PhD: Institute of Biophysics, Chinese Academy of Sciences
Recipient of the National Science Fund for Distinguished Young Scholars
2006-2009 - Dana-Farber Cancer Institute, Harvard University: Postdoctoral Researcher
2009-present - Tongji University, School of Life Sciences and Technology: Professor
2019-present - Department of Bioinformatics: Department Head
2013: National Science Fund for Distinguished Young Scholars
2015: Youth Top-notch Talent
2017: Shanghai Outstanding Academic Leader
2018: Ministry of Education Young Chang Jiang Scholar
2019: First Prize, Ministry of Education Natural Science Award
2020: Second Prize, National Natural Science Award
2022: First Prize, Shanghai Natural Science Award
2023: National Science Fund for Distinguished Young Scholars
Research
Bioinformatics
Mechanical strain treatment improves nuclear transfer reprogramming efficiency by enhancing chromatin accessibility, Chen Y, Xu R, Zhou S, Zhao C, Hu Z, Hua Y, Xiong Y, Liu X, Lv J, Sun Y, Li C, Gao S, Zhang Y, 2023
Allele-specific H3K9me3 and DNA methylation co-marked CpG-rich regions serve as potential imprinting control regions in pre-implantation embryo, Yang H, Bai D, Li Y, Yu Z, Wang C, Sheng Y, Liu W, Gao S, Zhang Y, 2022
Antibody-free profiling of transcription factor occupancy during early embryogenesis by FitCUT&RUN, Wang X, Wang W, Wang Y, Chen J, Liu G, Zhang Y, 2022
CpG island reconfiguration for the establishment and synchronization of polycomb functions upon exit from naive pluripotency, Huo D, Yu Z, Li R, Gong M, Sidoli S, Lu X, Hou Y, Dai Z, Kong Y, Liu G, Jensen O, Xie W, Helin K, Xiong C, Li G, Zhang Y, Wu X, 2022
Dynamic nucleosome organization after fertilization reveals regulatory factors for mouse zygotic genome activation, Wang C, Chen C, Liu X, Li C, Wu Q, Chen X, Yang L, Kou X, Zhao Y, Wang H, Gao Y, Zhang Y, Gao S, 2022
CStreet: a computed Cell State trajectory inference method for time-series single-cell RNA sequencing data, Zhao C, Xiu W, Hua Y, Zhang N, Zhang Y, Tuersunjiang N, Gao S, Liu W, 2021
Smarca5 mediated epigenetic programming facilitates fetal HSPC development in vertebrates, Ding Y, Wang W, Ma D, Liang G, Kang Z, Xue Y, Zhang Y, Wang L, Heng J, Zhang Y, Liu F, 2021
ncHMR detector: a computational framework to systematically reveal non-classical functions of histone modification regulators, Hu S, Huo D, Yu Z, Chen Y, Liu J, Liu L, Wu X, Zhang Y, 2020
A DNA methylation state transition model reveals the programmed epigenetic heterogeneity in human pre-implantation embryos, Zhao C, Zhang N, Zhang Y, Tuersunjiang N, Gao S, Liu W, 2020
Inherited DNA methylation primes the establishment of accessible chromatin during genome activation, Liu G, Wang W, Hu S, Wang X, Zhang Y, 2018
Reprogramming of H3K9me3-dependent heterochromatin during mammalian embryo development, Wang C, Liu X, Gao Y, Yang L, Li C, Liu W, Chen C, Kou X, Zhao Y, Chen J, Wang Y, Le R, Wang H, Duan T, Zhang Y, Gao S, 2018
Inhibition of aberrant DNA re-methylation improves the development of nuclear transfer embryos, Gao R, Wang C, Gao Y, Xiu W, Chen J, Kou X, Zhao Y, Liao Y, Bai D, Qiao Z, Yang L, Wang M, Zang R, Jia Y, Li Y, Yin J, Wang H, Wan X, Liu W, Zhang Y, Gao S, 2018
Distinct features of H3K4me3 and H3K27me3 chromatin domains in pre-implantation embryos, Liu X, Wang C, Liu W, Li J, Li C, Kou X, Chen J, Zhao Y, Gao H, Wang H, Zhang Y, Gao Y, Gao S, 2016
Dr.seq: a quality control and analysis pipeline for droplet sequencing, Huo X, Hu S, Zhao C, Zhang Y, 2016
Comprehensive profiling reveals mechanisms of SOX2-mediated cell fate specification in human ESCs and NPCs, Zhou C, Yang X, Sun Y, Yu H, Zhang Y, Jin Y, 2016
Identification of key factors conqueringdevelopmental arrest of somatic cell cloned embryos by combining embryo biopsy and single-cell sequencing, Liu W, Liu X, Wang C, Gao Y, Gao R, Kou X, Zhao Y, Li J, Wu Y, Xiu W, Wang S, Yin J, Liu W, Cai T, Wang H, Zhang Y, Gao S, 2016
SETDB1 modulates PRC2 activity at developmental genes independent of H3K9 trimethylation in mouse ES cells, Fei Q, Yang X, Jiang H, Wang Q, Yu Y, Yu Y, Yi W, Zhou S, Chen T, Lu C, Atadja P, Liu XS, Li E, Zhang Y, Shou J, 2015
Canonical nucleosome organization at promoters forms during genome activation, Zhang Y, Vastenhouw NL, Feng J, Fu K, Wang C, Ge Y, Pauli A, van Hummelen P, Schier AF, Liu XS, 2014
CR Cistrome: a ChIP-Seq database for chromatin regulators and histone modification linkages in human and mouse, Wang Q, Huang J, Sun H, Liu J, Wang J, Wang Q, Qin Q, Mei S, Zhao C, Yang X, Liu XS, Zhang Y, 2014
MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes, Zheng X, Zhao Q, Wu HJ, Li W, Wang H, Meyer CA, Qin QA, Xu H, Zang C, Jiang P, Li F, Hou Y, He J, Wang J, Wang J, Zhang P, Zhang Y, Liu XS, 2014
Target analysis by integration of transcriptome and ChIP-seq data with BETA, Wang S, Sun Hanfei, Ma J, Zang C, Wang C, Wang J, Tang Q, Meyer CA, Zhang Y, Liu XS, 2013
GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data, Feng J, Meyer CA, Wang Q, Liu JS, Liu XS, Zhang Y, 2012
DiNuP: a systematic approach to identify regions of differential nucleosome positioning, Fu K, Tang Q, Feng J, Liu XS, Zhang Y, 2012
Identifying ChIP-seq enrichment using MACS, Feng J, Liu T, Qin Bo, Zhang Y, Liu XS, 2012
Chromatin signature of embryonic pluripotency is established during zygotic genome activation, Vastenhouw NL, Zhang Y, Woods IG, Imam F, Regev A, X. Liu XS, Rinn J, Schier A, 2010
Intrinsic histone-DNA interactions are not the major determinant of nucleosome positions in vivo, Zhang Y, Moqtaderi Z, Rattner B, Euskirchen G, Snyder M, Kadonaga JT, Liu XS, Struhl K, 2009
Model-based analysis of ChIP-Seq (MACS), Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DJ, Myers RM, Bernstein BE, Nussbaum C, Brown M, Li W, Liu XS, 2008
Keywords
BioinformaticsTranscriptional RegulationCell FateEpigenomicsArtificial IntelligenceAlgorithm DevelopmentGenomic Data AnalysisEmbryonic DevelopmentHeterogeneityRegulatory Mechanisms
Area of Focus
Cell Fate | Epigenetics | High-Throughput Data | Single-Cell | Multi-Omics | Deep Learning | Transcriptomics | Machine Learning | Data Integration | Algorithm Development
