11 citations · 11 across the 6 of their papers we have counts for
6 papers
BioNeuralNet: A Graph Neural Network based Multi-Omics Network Data Analysis Tool
Vicente Ramos, Sundous Hussein, Mohamed Abdel-Hafiz +6
Multi-omics data offer unprecedented insights into complex biological systems, yet their high dimensionality, sparsity, and intricate interactions pose significant analytical chall…
Extensions of Heterogeneity in Integration and Prediction (HIP) with R Shiny Application
J. Butts, C. Wendt, R. Bowler +4
Multiple data views measured on the same set of participants is becoming more common and has the potential to deepen our understanding of many complex diseases by analyzing these d…
Robust Integrative Biclustering for Multi-view Data
W. Zhang, C. Wendt, R. Bowler +2
In many biomedical research, multiple views of data (e.g., genomics, proteomics) are available, and a particular interest might be the detection of sample subgroups characterized b…
Accounting for data heterogeneity in integrative analysis and prediction methods: An application to Chronic Obstructive Pulmonary Disease
J. Butts, C. Wendt, R. Bowler +4
Epidemiologic and genetic studies in chronic obstructive pulmonary disease (COPD) and many complex diseases suggest subgroup disparities (e.g., by sex). We consider this problem fr…
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…
Bayesian Inference of Networks Across Multiple Sample Groups and Data Types
Elin Shaddox, Christine B. Peterson, Francesco C. Stingo +5
In this paper, we develop a graphical modeling framework for the inference of networks across multiple sample groups and data types. In medical studies, this setting arises wheneve…