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Journal of Bioinformatics and Computational Biology|July 18, 2013
A variational Bayes beta mixture model for feature selection in DNA methylation studiesZhanyu Ma, Andrew E TeschendorffInternational Journal of Molecular Sciences|June 18, 2014
Comparisons of non-Gaussian statistical models in DNA methylation analysisZhanyu Ma, Andrew E Teschendorff, Hong Yu, et al.IEEE Transactions on Pattern Analysis and Machine Intelligence|September 10, 2015
Variational Bayesian Matrix Factorization for Bounded Support DataZhanyu Ma, Andrew E Teschendorff, Arne Leijon, et al.Biochemical Society Transactions|June 10, 2024
Computational single-cell methods for predicting cancer riskAndrew E TeschendorffGenome Medicine|June 26, 2020
A comparison of epigenetic mitotic-like clocks for cancer risk predictionAndrew E TeschendorffPhilosophical Transactions of the Royal Society of London. Series B, Biological Sciences|March 3, 2024
On epigenetic stochasticity, entropy and cancer riskAndrew E TeschendorffBMC Systems Biology|August 3, 2010
Increased entropy of signal transduction in the cancer metastasis phenotypeAndrew E Teschendorff, Simone SeveriniBioinformatics (Oxford, England)|April 12, 2012
Differential variability improves the identification of cancer risk markers in DNA methylation studies profiling precursor cancer lesionsAndrew E Teschendorff, Martin WidschwendterBreast Cancer Research : BCR|April 7, 2009
The breast cancer somatic 'muta-ome': tackling the complexityAndrew E Teschendorff, Carlos CaldasMethods in Molecular Biology (Clifton, N.J.)|February 14, 2019
Estimating Differentiation Potency of Single Cells Using Single-Cell Entropy (SCENT)Weiyan Chen, Andrew E TeschendorffPageof 20