High Performance Parallel/Distributed Biclustering Using Barycenter Heuristic.

Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and collaborative filtering. Due to requirements for high performance in large scale data processing applications such as Collaborative filtering in E-commerce systems and large scale genome-wide gene expression analysis in microarray experiments, a high performance prallel/distributed solution for biclustering problem is highly desirable. Recently, Ahmad et al [1] showed that Bipartite Spectral Partitioning, which is a popular technique for biclustering, can be reformulated as a graph drawing problem where objective is to minimize Hall’s energy of the bipartite graph representation of the input data. They showed that optimal solution to this problem is achieved when nodes are placed at the barycenter of their neighbors. In this paper, we provide a parallel algorithm for biclustering based on this formulation. ...

• Type: Conference
• Year: 2009
• Where: SDM
• Authors: Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-keng Liao
• Keywords: Computer Science, Gene Expression Analysis, Parallel Algorithm, Parallel Energy Minimization, SDM 2009