Search Results - "Allen, Genevera"

Thresholded graphical lasso adjusts for latent variables by Wang, Minjie, Allen, Genevera I

“…Summary Structural learning of Gaussian graphical models in the presence of latent variables has long been a challenging problem. Chandrasekaran et al. (2012)…”
Get full text

Tensor network factorizations: Relationships between brain structural connectomes and traits by Zhang, Zhengwu, Allen, Genevera I., Zhu, Hongtu, Dunson, David

“…Advanced brain imaging techniques make it possible to measure individuals’ structural connectomes in large cohort studies non-invasively. Given the…”
Get full text

Graphical Model Inference with Erosely Measured Data by Zheng, Lili, Allen, Genevera I.

“…In this article, we investigate the Gaussian graphical model inference problem in a novel setting that we call erose measurements, referring to irregularly…”
Get full text

Fast and interpretable consensus clustering via minipatch learning by Gan, Luqin, Allen, Genevera I

“…Consensus clustering has been widely used in bioinformatics and other applications to improve the accuracy, stability and reliability of clustering results…”
Get full text

Supervised convex clustering by Wang, Minjie, Yao, Tianyi, Allen, Genevera I.

“…Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many…”
Get full text

TCGA2STAT: simple TCGA data access for integrated statistical analysis in R by Wan, Ying-Wooi, Allen, Genevera I, Liu, Zhandong

“…Massive amounts of high-throughput genomics data profiled from tumor samples were made publicly available by the Cancer Genome Atlas (TCGA). We have developed…”
Get full text

Convex Biclustering by Chi, Eric C., Allen, Genevera I., Baraniuk, Richard G.

“…In the biclustering problem, we seek to simultaneously group observations and features. While biclustering has applications in a wide array of domains, ranging…”
Get full text

Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization by Weylandt, Michael, Nagorski, John, Allen, Genevera I.

“…Convex clustering is a promising new approach to the classical problem of clustering, combining strong performance in empirical studies with rigorous…”
Get full text

A review of multivariate distributions for count data derived from the Poisson distribution by Inouye, David I., Yang, Eunho, Allen, Genevera I., Ravikumar, Pradeep

“…The Poisson distribution has been widely studied and used for modeling univariate count‐valued data. However, multivariate generalizations of the Poisson…”
Get full text

Quantifying cognitive resilience in Alzheimer's Disease: The Alzheimer's Disease Cognitive Resilience Score by Yao, Tianyi, Sweeney, Elizabeth, Nagorski, John, Shulman, Joshua M, Allen, Genevera I

“…Even though there is a clear link between Alzheimer's Disease (AD) related neuropathology and cognitive decline, numerous studies have observed that healthy…”
Get full text

Automatic Feature Selection via Weighted Kernels and Regularization by Allen, Genevera I.

“…Selecting important features in nonlinear kernel spaces is a difficult challenge in both classification and regression problems. This article proposes to…”
Get full text

Generalized Least-Square Matrix Decomposition by Allen, Genevera I., Grosenick, Logan, Taylor, Jonathan

“…Variables in many big-data settings are structured, arising, for example, from measurements on a regular grid as in imaging and time series or from…”
Get full text

Correlation Imputation for Single-Cell RNA-seq by Gan, Luqin, Vinci, Giuseppe, Allen, Genevera I

Get more information

Genomic region detection via Spatial Convex Clustering by Nagorski, John, Allen, Genevera I

“…Several modern genomic technologies, such as DNA-Methylation arrays, measure spatially registered probes that number in the hundreds of thousands across…”
Get full text

Interpretable Machine Learning for Discovery: Statistical Challenges and Opportunities by Allen, Genevera I, Gan, Luqin, Zheng, Lili

“…New technologies have led to vast troves of large and complex data sets across many scientific domains and industries. People routinely use machine learning…”
Get full text

Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes by Zheng, Lili, Allen, Genevera I.

“…High-dimensional Gaussian graphical models have been a powerful tool for learning connections or interaction patterns among a large number of variables. While…”
Get full text

Functional screening of lysosomal storage disorder genes identifies modifiers of alpha-synuclein neurotoxicity by Yu, Meigen, Ye, Hui, De-Paula, Ruth B, Mangleburg, Carl Grant, Wu, Timothy, Lee, Tom V, Li, Yarong, Duong, Duc, Phillips, Bridget, Cruchaga, Carlos, Allen, Genevera I, Seyfried, Nicholas T, Al-Ramahi, Ismael, Botas, Juan, Shulman, Joshua M

“…Heterozygous variants in the glucocerebrosidase (GBA) gene are common and potent risk factors for Parkinson's disease (PD). GBA also causes the autosomal…”
Get full text

Molecular pathway identification using biological network-regularized logistic models by Zhang, Wen, Wan, Ying-Wooi, Allen, Genevera I, Pang, Kaifang, Anderson, Matthew L, Liu, Zhandong

“…Selecting genes and pathways indicative of disease is a central problem in computational biology. This problem is especially challenging when parsing…”
Get full text

SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra by Han, Xu, Wang, Wanli, Ma, Li-Hua, AI-Ramahi, Ismael, Botas, Juan, MacKenzie, Kevin, Allen, Genevera I, Young, Damian W, Liu, Zhandong, Maletic-Savatic, Mirjana

“…Abstract Motivation Nuclear magnetic resonance spectroscopy (NMR) is widely used to analyze metabolites in biological samples, but the analysis requires…”
Get full text

Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity by Narayan, Manjari, Allen, Genevera I

“…Many complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is…”
Get full text