1.2k citations · 1.6k across the 7 of their papers we have counts for
7 papers
Sparse Canonical Correlation Analysis via Concave Minimization
Omid S. Solari, James B. Brown, Peter J. Bickel
A new approach to the sparse Canonical Correlation Analysis (sCCA)is proposed with the aim of discovering interpretable associations in very high-dimensional multi-view, i.e.observ…
BLOCCS: Block Sparse Canonical Correlation Analysis With Application To Interpretable Omics Integration
Omid Shams Solari, Rojin Safavi, James B. Brown
We introduce Block Sparse Canonical Correlation Analysis which estimates multiple pairs of canonical directions (together a "block") at once, resulting in significantly improved or…
Signed iterative random forests to identify enhancer-associated transcription factor binding
Karl Kumbier, Sumanta Basu, Erwin Frise +4
Standard ChIP-seq peak calling pipelines seek to differentiate biochemically reproducible signals of individual genomic elements from background noise. However, reproducibility alo…
Iterative Random Forests to detect predictive and stable high-order interactions
Sumanta Basu, Karl Kumbier, James B. Brown +1
Genomics has revolutionized biology, enabling the interrogation of whole transcriptomes, genome-wide binding sites for proteins, and many other molecular processes. However, indivi…
MODA: MOdule Differential Analysis for weighted gene co-expression network
Dong Li, James B. Brown, Luisa Orsini +3
Gene co-expression network differential analysis is designed to help biologists understand gene expression patterns under different condition. By comparing different gene co-expres…
Measuring reproducibility of high-throughput experiments
Qunhua Li, James B. Brown, Haiyan Huang +1
Reproducibility is essential to reliable scientific discovery in high-throughput experiments. In this work we propose a unified approach to measure the reproducibility of findings…