399 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Rice UniversityUS17 papers
- The University of Texas Health Science Center at HoustonUS17 papers
- The University of Texas at AustinUS13 papers
- Harvard UniversityUS12 papers
- Baylor College of MedicineUS10 papers
- The University of Texas Southwestern Medical CenterUS9 papers
- University of PennsylvaniaUS8 papers
- Massachusetts General HospitalUS7 papers
- Stanford UniversityUS7 papers
- Technical University of MunichDE7 papers
- University of Alabama at BirminghamUS7 papers
- University of North Carolina at Chapel HillUS7 papers
23 papers · 1 filter
Sparse tree-based clustering of microbiome data to characterize microbiome heterogeneity in pancreatic cancer
Yushu Shi, Liangliang Zhang, Kim-Anh Do +2
There is a keen interest in characterizing variation in the microbiome across cancer patients, given increasing evidence of its important role in determining treatment outcomes. He…
A Bayesian Feature Allocation Model for Identification of Cell Subpopulations Using Cytometry Data
Arthur Lui, Juhee Lee, Peter F. Thall +3
A Bayesian feature allocation model (FAM) is presented for identifying cell subpopulations based on multiple samples of cell surface or intracellular marker expression level data o…
NExUS: Bayesian simultaneous network estimation across unequal sample sizes
Priyam Das, Christine Peterson, Kim-Anh Do +2
Network-based analyses of high-throughput genomics data provide a holistic, systems-level understanding of various biological mechanisms for a common population. However, when esti…
Bayesian Hierarchical Spatial Model for Small Area Estimation with Non-ignorable Nonresponses and Its Applications to the NHANES Dental Caries Assessments
Ick Hoon Jin, Fang Liu, Evercita C. Eugenio +2
The National Health and Nutrition Examination Survey (NHANES) is a major program of the National Center for Health Statistics, designed to assess the health and nutritional status…
Tensor network factorizations: Relationships between brain structural connectomes and traits
Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu +1
Advanced brain imaging techniques make it possible to measure individuals' structural connectomes in large cohort studies non-invasively. The structural connectome is initially sha…
Bayesian estimation of a semiparametric recurrent event model with applications to the penetrance estimation of multiple primary cancers in Li-Fraumeni Syndrome
Seung Jun Shin, Jialu Li, Jing Ning +3
A common phenomenon in cancer syndromes is for an individual to have multiple primary cancers at different sites during his/her lifetime. Patients with Li-Fraumeni syndrome (LFS),…
Bayesian Variable Selection For Survival Data Using Inverse Moment Priors
Amir Nikooienejad, Wenyi Wang, Valen E. Johnson
Efficient variable selection in high-dimensional cancer genomic studies is critical for discovering genes associated with specific cancer types and for predicting response to treat…
Bayesian Semiparametric Estimation of Cancer-specific Age-at-onset Penetrance with Application to Li-Fraumeni Syndrome
Seung Jun Shin, Ying Yuan, Louise C. Strong +2
Penetrance, which plays a key role in genetic research, is defined as the proportion of individuals with the genetic variants (i.e., {genotype}) that cause a particular trait and w…
A Nonparametric Bayesian Basket Trial Design
Yanxun Xu, Peter Mueller, Apostolia M Tsimberidou +1
Targeted therapies on the basis of genomic aberrations analysis of the tumor have shown promising results in cancer prognosis and treatment. Regardless of tumor type, trials that m…
Dynamic Prediction for Multiple Repeated Measures and Event Time Data: An Application to Parkinson's Disease
Jue Wang, Sheng Luo, Liang Li
In many clinical trials studying neurodegenerative diseases such as Parkinson's disease (PD), multiple longitudinal outcomes are collected to fully explore the multidimensional imp…
The Gibbs-plaid biclustering model
Thierry Chekouo, Alejandro Murua, Wolfgang Raffelsberger
We propose and develop a Bayesian plaid model for biclustering that accounts for the prior dependency between genes (and/or conditions) through a stochastic relational graph. This…
Combining nonexchangeable functional or survival data sources in oncology using generalized mixture commensurate priors
Thomas A. Murray, Brian P. Hobbs, Bradley P. Carlin
Conventional approaches to statistical inference preclude structures that facilitate incorporation of supplemental information acquired from similar circumstances. For example, the…
A Decision-Theoretic Comparison of Treatments to Resolve Air Leaks After Lung Surgery Based on Nonparametric Modeling
Yanxun Xu, Peter F. Thall, Peter Mueller +1
We propose a Bayesian nonparametric utility-based group sequential design for a randomized clinical trial to compare a gel sealant to standard care for resolving air leaks after pu…
Bayesian Nonparametric Estimation for Dynamic Treatment Regimes with Sequential Transition Times
Yanxun Xu, Peter Mueller, Abdus S. Wahed +1
Dynamic treatment regimes in oncology and other disease areas often can be characterized by an alternating sequence of treatments or other actions and transition times between dise…
Bayesian data augmentation dose finding with continual reassessment method and delayed toxicity
Suyu Liu, Guosheng Yin, Ying Yuan
A major practical impediment when implementing adaptive dose-finding designs is that the toxicity outcome used by the decision rules may not be observed shortly after the initiatio…
Network Inference Using Steady State Data and Goldbeter-Koshland Kinetics
Chris J Oates, Bryan T Hennessy, Yiling Lu +2
Network inference approaches are widely used to shed light on regulatory interplay between molecular players such as genes and proteins. Biochemical processes underlying networks o…
Bayesian modeling longitudinal dyadic data with nonignorable dropout, with application to a breast cancer study
Guangyu Zhang, Ying Yuan
Dyadic data are common in the social and behavioral sciences, in which members of dyads are correlated due to the interdependence structure within dyads. The analysis of longitudin…
Modeling dependent gene expression
Donatello Telesca, Peter Müller, Giovanni Parmigiani +1
In this paper we propose a Bayesian approach for inference about dependence of high throughput gene expression. Our goals are to use prior knowledge about pathways to anchor infere…
Automated analysis of quantitative image data using isomorphic functional mixed models, with application to proteomics data
Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Richard C. Herrick +2
Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensiti…
Bayesian phase I/II adaptively randomized oncology trials with combined drugs
Ying Yuan, Guosheng Yin
We propose a new integrated phase I/II trial design to identify the most efficacious dose combination that also satisfies certain safety requirements for drug-combination trials. W…
Sparse logistic principal components analysis for binary data
Seokho Lee, Jianhua Z. Huang, Jianhua Hu
We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the pro…
Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology
Keith A. Baggerly, Kevin R. Coombes
High-throughput biological assays such as microarrays let us ask very detailed questions about how diseases operate, and promise to let us personalize therapy. Data processing, how…
A Bayesian semi-parametric model for small area estimation
Donald Malec, Peter Müller
In public health management there is a need to produce subnational estimates of health outcomes. Often, however, funds are not available to collect samples large enough to produce…