|Title||Getting High-throughput Arrays in Order with Convex Biclustering|
|Year of Publication||2016|
In the biclustering problem, we seek to simultaneously group observations and features. We present a convex formulation of the biclustering problem that possesses a unique global minimizer and an iterative algorithm, COBRA, that is guaranteed to identify it. The key contributions of our work are its simplicity, interpretability, and algorithmic guarantees. We demonstrate the advantages of our approach, which includes stably and reproducibly identifying biclusterings, on simulated and real high-throughput data.