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Christopher Yau
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Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis
EP-653 Diagnosing Acute Appendicitis using Machine Learning: A Systematic Review
In simulated data and health records, latent class analysis was the optimum multimorbidity clustering algorithm
Rarity: Discovering rare cell populations from single-cell imaging data
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
Author Correction: Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed
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 pan-cancer genome-wide analysis reveals tumour dependencies by induction of nonsense-mediated decay
Bayesian Boolean matrix factorisation
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
Abstract LB-340: A novel method for estimating somatic mutations cellular prevalence in cancer using whole genome haplotype phasing
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 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
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
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