Intersected coexpressed subcube miner: An effective triclustering algorithm

Triclustering techniques extract genes that have similar expression patterns in a set of samples across a set of time points. A challenge in triclustering is to account for both inter-temporal and intra-temporal gene coherence. Other challenges include avoidance of time-dominated and sample-dominated results and detection of time latent triclusters. This paper presents a technique based on order preserving sub-matrices to find a set of triclusters from gene-sample-time data. The technique finds a set of initial modules in each unordered pair of gene-sample planes, which are then extended to final triclusters. We propose a planar similarity measure called PMRS to extend the initial modules to the final triclusters.