Christopher Yau

Latest

• Association between pregnancy-related complications and development of type 2 diabetes and hypertension in women: an umbrella review
• Bayesian inference for identifying tumour-specific cancer dependencies through integration of ex-vivo drug response assays and drug-protein profiling
• Correction: Completing a genomic characterisation of microscopic tumour samples with copy number
• Disentangling shared and private latent factors in multimodal Variational Autoencoders
• TransfoRNA: Navigating the Uncertainties of Small RNA Annotation with an Adaptive Machine Learning Strategy
• Artificial Intelligence for Multiple Long-term conditions (AIM): A consensus statement from the NIHR AIM consortia
• Completing a genomic characterisation of microscopic tumour samples with copy number
• Identifying factors associated with user retention and outcomes of a digital intervention for substance use disorder: a retrospective analysis of real-world data
• On the Difficulty of Predicting Engagement with Digital Health for Substance Use
• Polypharmacy during pregnancy and associated risk factors: a retrospective analysis of 577 medication exposures among 1.5 million pregnancies in the UK, 2000-2019
• Rarity: discovering rare cell populations from single-cell imaging data
• A multi-resolution framework for U-Nets with applications to hierarchical VAEs
• Derivative-based neural modelling of cumulative distribution functions for survival analysis
• Feature allocation approach for multimorbidity trajectory modelling
• In simulated data and health records, latent class analysis was the optimum multimorbidity clustering algorithm
• mmVAE: multimorbidity clustering using Relaxed Bernoulli $ $β$ $-Variational Autoencoders
• Protocol for development and validation of postpartum cardiovascular disease (CVD) risk prediction model incorporating reproductive and pregnancy-related candidate predictors
• An interpretable meta-clustering framework for single-cell RNA-Seq data integration and evaluation
• Associations between baseline opioid use disorder severity, mental health and biopsychosocial functioning, with clinical responses to computer-assisted therapy treatment
• Basisdevae: Interpretable simultaneous dimensionality reduction and feature-level clustering with derivative-based variational autoencoders
• CIDER: an interpretable meta-clustering framework for single-cell RNA-seq data integration and evaluation
• Multi-facet clustering variational autoencoders
• Pan-cancer detection of driver genes at the single-patient resolution
• Protocol for the development of a core outcome set for studies of pregnant women with pre-existing multimorbidity
• A highly accurate platform for clone-specific mutation discovery enables the study of active mutational processes
• BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders
• How Has the COVID-19 Pandemic Changed How You Will Approach Research and Lab Work in the Future?
• Neural decomposition: Functional anova with variational autoencoders
• A descriptive marker gene approach to single-cell pseudotime inference
• Augmented ensemble mcmc sampling in factorial hidden markov models
• Bayesian Nonparametric Boolean Factor Models
• Bayesian statistical learning for big data biology
• Decomposing feature-level variation with covariate Gaussian process latent variable models
• Deep single-cell RNA-seq of the putative cell of origin revealed a novel molecular subtype of high-grade serous ovarian cancer with poor prognosis
• Immunophenotypes of pancreatic ductal adenocarcinoma: Meta-analysis of transcriptional subtypes
• Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma
• Uncovering the long tail of oesophageal cancer driver genes for patient stratification
• DigiPico: A whole-genome sequencing approach to investigate microscopic residual chemotherapy resistance disease in ovarian cancer
• Integrated single cell analysis reveals cell cycle and ontogeny related transcriptional heterogeneity in HSCs
• MixDir: scalable Bayesian clustering for high-dimensional categorical data
• Probabilistic Boolean Tensor Decomposition
• Separation of dual oxidase 2 and lactoperoxidase expression in intestinal crypts and species differences may limit hydrogen peroxide scavenging during mucosal healing in mice and humans
• Uncovering pseudotemporal trajectories with covariates from single cell and bulk expression data
• A descriptive marker gene approach to single-cell pseudotime
• A pan-cancer genome-wide analysis reveals tumour dependencies by induction of nonsense-mediated decay
• Bayesian boolean matrix factorisation
• Money that no one wants to pay or receive: engaging for safety: Report to the Health Foundation
• Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers
• switchde: inference of switch-like differential expression along single-cell trajectories
• Testing and learning on distributions with symmetric noise invariance
• The Hamming ball sampler
• Unravelling cell cycle and ontogeny transcriptional heterogeneity in hematopoietic stem cells through integrated single cell RNA-seq
• Order under uncertainty: robust differential expression analysis using probabilistic models for pseudotime inference
• pcaReduce: hierarchical clustering of single cell transcriptional profiles
• Statistical inference in hidden Markov models using k-segment constraints
• The alive particle filter and its use in particle Markov chain Monte Carlo
• ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis
• A sequential algorithm for fast fi fitting of Dirichlet process mixture models
• Hamming ball auxiliary sampling for factorial hidden Markov models
• Towards Response Prediction Using Integrated Genomics in Chronic Lymphocytic Leukaemia: Results on 250 First-Line FCR Treated Patients from UK Clinical Trials
• A decision-theoretic approach for segmental classification
• Analysis of colorectal cancers in British Bangladeshi identifies early onset, frequent mucinous histotype and a high prevalence of RBFOX1 deletion
• NucleoFinder: a statistical approach for the detection of nucleosome positions
• OncoSNP-SEQ: a statistical approach for the identification of somatic copy number alterations from next-generation sequencing of cancer genomes
• Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination
• A statistical approach for detecting genomic aberrations in heterogeneous tumor samples from single nucleotide polymorphism genotyping data
• On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods
• Presynaptic NMDARs in the hippocampus facilitate transmitter release at theta frequency
• Bayesian nonparametric hidden Markov models with application to the analysis of copy-number-variation in mammalian genomes
• Comparing CNV detection methods for SNP arrays
• A genotype calling algorithm for the illumina beadarray platform
• A recursive, stochastic vessel segmentation framework that robustly handles bifurcations
• Akt regulates centrosome migration and spindle orientation in the early Drosophila melanogaster embryo
• GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population
• Statistical methodologies for the identification of copy number variation in mammalian genomes from high-throughput genomic datasets
• QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data
• Quantitative image analysis of chromosome dynamics in early Drosophila embryos