42 citations · 159 across the 15 of their papers we have counts for
5 papers · 1 filter
Bayesian Inference for Tumor Subclones Accounting for Sequencing and Structural Variants
Juhee Lee, Peter Mueller, Subhajit Sengupta +2
Tumor samples are heterogeneous. They consist of different subclones that are characterized by differences in DNA nucleotide sequences and copy numbers on multiple loci. Heterogene…
A Latent Gaussian Process Model with Application to Monitoring Clinical Trials
Yanxun Xu, Yuan Ji
In many clinical trials treatments need to be repeatedly applied as diseases relapse frequently after remission over a long period of time (e.g., 35 weeks). Most research in statis…
Bayesian sparse graphical models for classification with application to protein expression data
Veerabhadran Baladandayuthapani, Rajesh Talluri, Yuan Ji +5
Reverse-phase protein array (RPPA) analysis is a powerful, relatively new platform that allows for high-throughput, quantitative analysis of protein networks. One of the challenges…
Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials
Yanxun Xu, Lorenzo Trippa, Peter Müller +1
Targeted therapies based on biomarker profiling are becoming a mainstream direction of cancer research and treatment. Depending on the expression of specific prognostic biomarkers,…
MAD Bayes for Tumor Heterogeneity Feature Allocation with Non-Normal Sampling
Yanxun Xu, Peter Mueller, Yuan Yuan +2
We propose small-variance asymptotic approximations for the inference of tumor heterogeneity (TH) using next-generation sequencing data. Understanding TH is an important and open r…