Andrew E. Teschendorff

Andrew E. Teschendorff, Ph.D.

Professor

Principal Investigator

Laboratory of Computational Systems Epigenomics

CAS-MPG Partner Institute for Computational Biology

Shanghai Institute of Nutrition and Health

Shanghai Institute for Biological Sciences

University of Chinese Academy of Sciences

Chinese Academy of Sciences, China

About the Speaker:

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.

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

Education

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 Recent Publications:

1. Garmire LX, Li Y, Huang Q, Xu C, Teichmann SA, Kaminski N, Pellegrini M, Nguyen Q, Teschendorff AE (2024) Challenges and perspectives in computational deconvolution of genomics data. Nat Methods 21:391-400.

2. Maity AK, Teschendorff AE (2023) Cell-attribute aware community detection improves differential abundance testing from single-cell RNA-Seq data. Nat Commun 14:3244.

3. Zhu T, Liu J, Beck S, Pan S, Capper D, Lechner M, Thirlwell C, Breeze CE, Teschendorff AE (2022) A pan-tissue DNA methylation atlas enables in-silico decomposition of human tissue methylomes at cell-type resolution. Nat Methods 19:296-306.

4. CNCB-NGDC Members and Partners (2022) Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022. Nucleic Acids Res 50(D1).

5. Teschendorff AE, Feinberg AP (2021) Statistical mechanics meets single-cell biology. Nat Rev Genet 22:459-476.