Isomorphic Subgraph for Identification of Singleton Attractors in Boolean Networks

Punase, Santosh Rout, Ranjeet KumarThe various interactions between organic components, for example, genes, proteins, ribonucleic acid (RNA),, and metabolites organize biological systems and are responsible for cellular function. Biological systems are portrayed by a substantial number of components. The finding of attractors in such a system is of great significance to understand complex marvels. This paper proposes a sequential isomorphic subgraph (SISG) algorithm which reveals all the singleton attractors of a biological network, with much less computational cost as compared to explicit enumeration (EE) along with maintaining the accuracy. The novel feature of this work is that the computational cost to uncover the number of attractors in a biological network is directly proportional to the number of nodes in the networks. The SISG algorithm deconstructs the biological network into equal number of subgraphs as their in-degrees and then finds the isomorphic subgraphs. Algorithm reduces the computational cost by avoiding the redundant computation of finding the attractors of isomorphic subgraphs. The feasibility and efficiency of the proposed approach are illustrated in the result.