Finding Biclusters by Random Projections

Given a matrix X composed of symbols, a bicluster is a submatrix of X obtained by removing some of the rows and some of the columns of X in such a way that each row of what is left reads the same string. In this paper, we are concerned with the problem of finding the bicluster with the largest area in a large matrix X. The problem is first proved to be NP-complete. We present a fast and efficient randomized algorithm that discovers the largest bicluster by random projections. A detailed probabilistic analysis of the algorithm and an asymptotic study of the statistical significance of the solutions are given. We report results of extensive simulations on synthetic data. © 2006 Elsevier B.V. All rights reserved.

• Type: Conference
• Year: 2004
• Where: CPM
• Authors: Stefano Lonardi, Wojciech Szpankowski, Qiaofeng Yang
• Keywords: CPM 2004, Efficient Randomized Algorithm, Large Matrix X, Matrix