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Professor, Principal Investigator

Laboratory of Computational Systems Epigenomics

Lab Page Link: https://aet21.github.io

Email: andrew@sinh.ac.cn

Tel: 86-21-54920659

Research Areas:

My broad research interest is in Statistical Bioinformatics with a focus on Statistical Cancer Epigenomics and Cancer Systems Biology. The goal is to use novel advanced computational approaches to help understand oncogenesis and develop novel improved tools for risk prediction and early detection of common cancers.


Brief Biography:

Work Experience

01/2020- at present: Professor in Computational Systems Epigenomics. Principal Investigator of Shanghai Institute of Nutrition and Health (SINH), CAS

09/2013-12/2019: Professor in Computational Systems Epigenomics, Principal Investigator of CAS-MPG Partner Institute for Computational Biology (PICB)

09/2015–Present: Honorary Research Fellow, UCL Cancer Institute, University College London, UK

09/2008–09/2013: UCL Cancer Institute, University College London, UK

2015–2019: Royal Society Newton Advanced Fellow

09/2003–08/2008: Senior Postdoctoral Fellow in Computational Biology, Breast Cancer Functional Genomics Laboratory headed by Professor Carlos Caldas, University of Cambridge, Department of Oncology

08/2001–08/2003: Research Assistant in Mathematical Ecology, based within the Mathematical Biology Group headed by Professor David A. Rand, University of Warwick, Mathematics Institute

06/2000-07/2001: Member of the Complexity Research Group headed by Dr Sverrir Olafsson, British Telecom Labs, Complexity Research


PhD Theoretical Particle Physics, University of Cambridge, May 2000.

Certificate of Advanced Study in Mathematics, University of Cambridge, Awarded Distinction, July 1996.

BSc (Hon) Mathematical Physics, University of Edinburgh, Awarded 1st Class, July 1995.


Selected Publications: (*Corresponding Author)

  1. Luo Q#, Dwaraka VB#, Chen Q#, Tong H, Zhu T, Seale K, Raffaele JM, Zheng SC, Mendez TL, Chen Y, Carreras N, Begum S, Mendez K, Voisin S, Eynon N, Lasky-Su JA*, Smith R*, Teschendorff AE*. A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes. Genome Med 2023 Jul 31;15(1):59
  2. Maity AK, Teschendorff AE*. Cell-attribute aware community detection improves differential abundance testing from single-cell RNA-Seq data. Nat Commun 2023 Jun 5;14(1):3244
  3. Liu T#, Zhao X#, Lin Y#, Luo Q#, Zhang S#, Xi Y, Chen Y, Lin L, Fan W, Yang J, Ma Y, Maity AK, Huang Y, Wang J, Chang J*, Lin D*, Teschendorff AE*, Wu C*. Computational Identification of Preneoplastic Cells Displaying High Stemness and Risk of Cancer Progression. Cancer Res 2022 Jul 18;82(14):2520-2537
  4. Zhu TY, Liu J, Beck S, Pan S, Capper D, Lechner M, Thirlwell C, Breeze CE*, Teschendorff AE*. A pan-tissue DNA methylation atlas enables in-silico decomposition of human tissue methylomes at cell-type resolution. Nat Methods 2022 Mar 11;19(3):296-306
  5. Teschendorff AE*, Feinberg AP. Statistical mechanics meets single-cell biology. Nat Rev Genet 2021 Jul;22(7):459-476
  6. Teschendorff AE*, Maity AK, Hu X, Weiyan C, Lechner M. Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data. Bioinformatics 2021 Jul 12;37(11):1528-1534
  7. You C, Wu S, Zheng SC, Zhu T, Jing H, Flagg K, Wang G, Jin L, Wang S, Teschendorff AE*. A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes. Nat Commun 2020 Sep 22;11(1):4779
  8. Chen W, Morabito SJ, Kessenbrock K, Enver T, Meyer KB, Teschendorff AE*. Single-cell landscape in mammary epithelium reveals bipotent-like cells associated with breast cancer risk and outcome. Commun Biol 2019 Aug 9;2:306
  9. Zheng SC, Breeze CE, Beck S, Teschendorff AE*. Identification of differentially methylated cell types in epigenome-wide association studies. Nat Methods 2018 Dec;15(12):1059-1066
  10. Teschendorff AE*, Relton CL. Statistical and integrative system-level analysis of DNA methylation data. Nat Rev Genet 2018 Mar;19(3):129-147
  11. Teschendorff AE*, Enver T. Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome. Nat Commun 2017 Jun 1;8:15599
  12. Zheng SC, Beck S, Jaffe AE, Koestler DC, Hansen KD, Houseman AE, Irizarry RA, Teschendorff AE*. Correcting for cell-type heterogeneity in epigenome-wide association studies: revisiting previous analyses. Nat Methods 2017 Feb 28;14(3):216-217
  13. Teschendorff AE*, Gao Y, Jones A, Ruebner M, Beckmann MW, Wachter DL, Fasching PA, Widschwendter M. DNA methylation outliers in normal breast tissue identify field defects that are enriched in cancer. Nat Commun 2016 Jan 29;7:10478
  14. Teschendorff AE*, Yang Z, Wong A, Pipinikas CP, Jiao Y, Jones A, Anjum S, Hardy R, Salvesen HB, Thirlwell C, Janes SM, Kuh D, Widschwendter M. Correlation of Smoking-Associated DNA Methylation Changes in Buccal Cells With DNA Methylation Changes in Epithelial Cancer. JAMA Oncol 2015 Jul;1(4):476-485
  15. Teschendorff AE*, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, Beck S. A Beta-Mixture Quantile Normalisation method for correcting probe design bias in Illumina Infinium 450k DNA methylation data. Bioinformatics 2013 Jan 15;29(2):189-196