321 citations · 350 across the 3 of their papers we have counts for
4 papers
High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient
Amir Asiaee, Samet Oymak, Kevin R. Coombes +1
We consider the problem of multi-task learning in the high dimensional setting. In particular, we introduce an estimator and investigate its statistical and computational propertie…
IntLIM: Integration using Linear Models of metabolomics and gene expression data
Jalal K. Siddiqui, Elizabeth Baskin, Mingrui Liu +6
Integration of transcriptomic and metabolomic data improves functional interpretation of disease-related metabolomic phenotypes, and facilitates discovery of putative metabolite bi…
Bayesian sparse graphical models for classification with application to protein expression data
Veerabhadran Baladandayuthapani, Rajesh Talluri, Yuan Ji +5
Reverse-phase protein array (RPPA) analysis is a powerful, relatively new platform that allows for high-throughput, quantitative analysis of protein networks. One of the challenges…
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…