26 citations · 29 across the 4 of their papers we have counts for
5 papers
Finding Groups of Cross-Correlated Features in Bi-View Data
Miheer Dewaskar, John Palowitch, Mark He +2
Datasets in which measurements of two (or more) types are obtained from a common set of samples arise in many scientific applications. A common problem in the exploratory analysis…
Computing the statistical significance of optimized communities in networks
John Palowitch
It is often of interest to find communities in network data for unsupervised learning, feature discovery, anomaly detection, or scientific study. The vast majority of community det…
Community extraction in multilayer networks with heterogeneous community structure
James D. Wilson, John Palowitch, Shankar Bhamidi +1
Multilayer networks are a useful way to capture and model multiple, binary or weighted relationships among a fixed group of objects. While community detection has proven to be a us…
Estimation of Interpretable eQTL Effect Sizes Using a Log of Linear Model
John Palowitch, Andrey Shabalin, Yihui Zhou +2
The study of expression Quantitative Trait Loci (eQTL) is an important problem in genomics and biomedicine. While detection (testing) of eQTL associations has been widely studied,…
Significance-based community detection in weighted networks
John Palowitch, Shankar Bhamidi, Andrew B. Nobel
Community detection is the process of grouping strongly connected nodes in a network. Many community detection methods for un-weighted networks have a theoretical basis in a null m…