602 citations · 1.2k across the 21 of their papers we have counts for
23 papers
Multiple Augmented Reduced Rank Regression for Pan-Cancer Analysis
Jiuzhou Wang, Eric F. Lock
Statistical approaches that successfully combine multiple datasets are more powerful, efficient, and scientifically informative than separate analyses. To address variation archite…
Bayesian Simultaneous Factorization and Prediction Using Multi-Omic Data
Sarah Samorodnitsky, Chris H. Wendt, Eric F. Lock
Understanding of the pathophysiology of obstructive lung disease (OLD) is limited by available methods to examine the relationship between multi-omic molecular phenomena and clinic…
Bayesian predictive modeling of multi-source multi-way data
Jonathan Kim, Brian J. Sandri, Raghavendra B. Rao +1
We develop a Bayesian approach to predict a continuous or binary outcome from data that are collected from multiple sources with a multi-way (i.e.. multidimensional tensor) structu…
Multiway sparse distance weighted discrimination
Bin Guo, Lynn E. Eberly, Pierre-Gilles Henry +2
Modern data often take the form of a multiway array. However, most classification methods are designed for vectors, i.e., 1-way arrays. Distance weighted discrimination (DWD) is a…
A Hierarchical Spike-and-Slab Model for Pan-Cancer Survival Using Pan-Omic Data
Sarah Samorodnitsky, Katherine A. Hoadley, Eric F. Lock
Pan-omics, pan-cancer analysis has advanced our understanding of the molecular heterogeneity of cancer, expanding what was known from single-cancer or single-omics studies. However…
sJIVE: Supervised Joint and Individual Variation Explained
Elise F. Palzer, Christine Wendt, Russell Bowler +3
Analyzing multi-source data, which are multiple views of data on the same subjects, has become increasingly common in molecular biomedical research. Recent methods have sought to u…