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Andrew Teschendorff
andrew@sinh.ac.cn
English, Chinese
Shanghai
University of Chinese Academy of Sciences
Life Sciences
  • 1996-09--2000-07 PhD in Theoretical Physics: University of Cambridge
  • 1995-09--1996-07 MSc in Applied Mathematics: University of Cambridge
  • 1990-09--1995-07 BSc in Mathematical Physics: University of Edinburgh
  • 2020-04~Present - Chinese Academy of Sciences, Shanghai Institute of Nutrition and Health - PI of Computational Systems Genomics Group
  • 2013-09~2020-03 - CAS-MPG Partner Institute for Computational Biology - PI of Computational Systems Genomics Group
  • 2008-09~2013-08 - University College London, UCL Cancer Institute - Principal Research Associate in Statistical Cancer Genomics
  • 2003-09~2008-08 - University of Cambridge, Department of Oncology - Senior Postdoctoral Fellow in Computational Biology
  • 2001-08~2003-08 - University of Warwick, Mathematics Institute - Research Assistant in Mathematical Ecology
  • 2000-08~2001-07 - British Telecom Labs, Complexity Research - Member of the Complexity Research Group
  • Clarivate Highly Cited Researcher (2023): Other
  • CAS Excellent Teachers Award (2019): Institute
Computational Biology
Statistical Bioinformatics
  • Quantifying the stochastic component of epigenetic aging, Nature Aging, 2024
  • A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes, Genome Medicine, 2023
  • Insights into the role of long non-coding RNAs in DNA methylation mediated transcriptional regulation, FRONTIERS IN MOLECULAR BIOSCIENCES, 2022
  • Cell-type heterogeneity: Why we should adjust for it in epigenome and biomarker studies, CLINICAL EPIGENETICS, 2022
  • Novel epigenetic network biomarkers for early detection of esophageal cancer, CLINICAL EPIGENETICS, 2022
  • Distance covariance entropy reveals primed states and bifurcation dynamics in single-cell RNA-Seq data, ISCIENCE, 2022
  • Making sense of the ageing methylome, NATURE REVIEWS GENETICS, 2022
  • Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022, Nucleic Acids Research, 2022
  • Clinical outcomes, Kadish-INSICA staging and therapeutic targeting of somatostatin receptor 2 in olfactory neuroblastoma, EUROPEAN JOURNAL OF CANCER, 2022
  • Computational Identification of Preneoplastic Cells Displaying High Stemness and Risk of Cancer Progression, CANCER RESEARCH, 2022
  • Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations, GENOME BIOLOGY, 2022
  • A comparison of epithelial cell content of oral samples estimated using cytology and DNA methylation, EPIGENETICS, 2022
  • Inference of age-associated transcription factor regulatory activity changes in single cells, Nature aging, 2022
  • dbDEMC 3.0:Functional Exploration of Differentially Expressed miRNAs in Cancers of Human and Model Organisms, GENOMICS PROTEOMICS & BIOINFORMATICS, 2022
  • A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution, NATURE METHODS, 2022
  • Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data, BIOINFORMATICS, 2021
  • Pan-cancer characterization of long non-coding RNA and DNA methylation mediated transcriptional dysregulation, EBIOMEDICINE, 2021
  • Statistical mechanics meets single-cell biology, NATURE REVIEWS GENETICS, 2021
  • EPISCORE: cell type deconvolution of bulk tissue DNA methylomes from single-cell RNA-Seq data, GENOME BIOLOGY, 2020
  • A comparison of epigenetic mitotic-like clocks for cancer risk prediction, GENOME MEDICINE, 2020
  • EpiDISH web server: Epigenetic Dissection of Intra-Sample-Heterogeneity with online GUI, BIOINFORMATICS, 2020
  • Quantifying Waddington's epigenetic landscape: a comparison of single-cell potency measures, BRIEFINGS IN BIOINFORMATICS, 2020
  • A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes, NATURE COMMUNICATIONS, 2020
  • Improved detection of tumor suppressor events in single-cell RNA-Seq data, NPJ GENOMIC MEDICINE, 2020
  • Detection of epigenetic field defects using a weighted epigenetic distance-based method, NUCLEIC ACIDS RESEARCH, 2019
  • eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data, BIOINFORMATICS, 2019
  • ebGSEA: an improved Gene Set Enrichment Analysis method for Epigenome-Wide-Association Studies, BIOINFORMATICS, 2019
  • Appraising the causal relevance of DNA methylation for risk of lung cancer, INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2019
  • Single-cell landscape in mammary epithelium reveals bipotent-like cells associated with breast cancer risk and outcome, COMMUNICATIONS BIOLOGY, 2019
  • Avoiding common pitfalls in machine learning omic data science, NATURE MATERIALS, 2019
  • Accounting for differential variability in detecting differentially methylated regions, BRIEFINGS IN BIOINFORMATICS, 2019
  • DNA methylation aging clocks: challenges and recommendations, GENOME BIOLOGY, 2019
  • Statistical and integrative system-level analysis of DNA methylation data, NATURE REVIEWS GENETICS, 2018
  • A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix, EPIGENOMICS, 2018
  • Psychosocial adversity and socioeconomic position during childhood and epigenetic age: analysis of two prospective cohort studies, HUMAN MOLECULAR GENETICS, 2018
  • DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants, EBIOMEDICINE, 2018
  • Tumor origin detection with tissue-specific miRNA and DNA methylation markers, BIOINFORMATICS, 2018
  • Roadmap for investigating epigenome deregulation and environmental origins of cancer, INTERNATIONAL JOURNAL OF CANCER, 2018
  • Epigenome-based cancer risk prediction: rationale, opportunities and challenges, NATURE REVIEWS CLINICAL ONCOLOGY, 2018
  • Identification of differentially methylated cell-types in Epigenome-Wide Association Studies, NATURE METHODS, 2018
  • Cell and tissue type independent age-associated DNA methylation changes are not rare but common, AGING (ALBANY NY), 2018
  • Epigenetic clocks galore: a new improved clock predicts age-acceleration in Hutchinson Gilford Progeria Syndrome patients, AGING (ALBANY NY), 2018
  • Tensorial blind source separation for improved analysis of multi-omic data, GENOME BIOLOGY, 2018
  • ChAMP: updated methylation analysis pipeline for Illumina BeadChips, BIOINFORMATICS, 2017
  • A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies, BMC BIOINFORMATICS, 2017
  • Epigenetic and genetic deregulation in cancer target distinct signaling pathway domains, NUCLEIC ACIDS RESEARCH, 2017
  • Are objective measures of physical capability related to accelerated epigenetic age? Findings from a British birth cohort, BMJ OPEN, 2017
  • Cell-type deconvolution in epigenome-wide association studies: a review and recommendations, EPIGENOMICS, 2017
  • Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome, NATURE COMMUNICATIONS, 2017
  • dbDEMC 2.0: updated database of differentially expressed miRNAs in human cancers, NUCLEIC ACIDS RESEARCH, 2017
  • Correcting for cell-type heterogeneity in epigenome-wide association studies: revisiting previous analyses
Computational Biology Bioinformatics Genomics Epigenetics Cancer Research Single-Cell Analysis Statistical Methods Systems Biology Dna Methylation Aging

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