Computational Epigenomics
We focus on computational challenges in processing and interpreting cancer (epi)genomic data.
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Mingxiang Teng, PhD
Assistant Member |
Selected Publications
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Wang C†, Liu X†, Liang J†, Narita Y†, Ding W†, …, Jiang S*, Teng M*, Zhao B*. A DNA tumor virus globally reprograms host 3D genome architecture to achieve immortal growth. Nature Communications. 2023;14(1):1598.
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Liu X, Zhao B, Shaw TI, Fridley BL, Duckett DR, Tan AC, Teng M*. Summarizing internal dynamics boosts differential analysis and functional interpretation of super enhancers. Nucleic Acids Research. 2022;50(6):3115-3127.
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Teng M*, Du D, Chen D, Irizarry RA. Characterizing batch effects and binding site-specific variability in ChIP-seq data. NAR Genomics and Bioinformatics. 2021;3(4):lqab098.
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Wang C†, Zhang L†, Ke L, …, Kaye KM, Teng M*, Zhao B*. Primary effusion lymphoma enhancer connectome links super-enhancers to dependency factors. Nature Communications. 2020;11(1):6318.
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Guo R†, Jiang C†, Zhang Y, …, Doench JG, Teng M*, Gewurz BE*. MYC controls the Epstein-Barr Virus lytic switch. Molecular Cell. 2020;78(4):653-669.e8.
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Teng M, Irizarry RA*. Accounting for GC-content bias reduces systematic errors and batch effects in ChIP-seq data. Genome Research. 2017;27(11):1930-1938.
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Teng M, Love MI, …, Irizarry RA*. A benchmark for RNA-seq quantification pipelines. Genome Biology. 2016;17:74.