Network analysis of normal and bipartite networks

Abstract

Enumerating maximal bicliques is essential to analyze several biological networks. For example bicliques in gene expression data helps us to maps a set of genes to their biological function. Statistical methods have been used to solve some the problems, however because of the diverse nature of data there is need for a combinatorial method. In this work we will suggest improvement to the state of the art algorithm iMBEA by Zhang, Yun, et al. for biclique enumeration.We use ideas used in clique enumeration, which has been studied more that biclique enumeration to improve the current state of the art of biclique enumeration algorithm iMBEA.