Background: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem...
Peter A. DiMaggio Jr., Scott R. McAllister, Christ...
Clustering has been one of the most popular approaches used in gene expression data analysis. A clustering method is typically used to partition genes according to their similarity...
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
A good number of biclustering algorithms have been proposed for grouping gene expression data. Many of them have adopted matrix norms to define the similarity score of a bicluste...
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 co...
Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...