A Generalization of Gene Network Representation on the Hypercube

Pabel Shahrear1,Email

Ummey Habiba1

Shajedul Karim1

Rezwan Shahrear

1Department of Mathematics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh.

2Canada revenue agency, surrey, BC V3T 5E1 Canada.


This article emphasizes the relation between Boolean input variables and Boolean states since the complexity of such connectivity increases enormously. Graphically, genetic systems up to 4-dimensional states of the implementation on hypercubes are accessible because the visibility of genetic systems up to 4-dimension on a hypercube is not laborious. The state connection on a hypercube is inflexible and only possible if the input variables are higher or more significant, for example, N ≥ 6. We have explored similar relations in this manuscript for higher dimensions. An algorithm is developed in the form of a matrix such that the connections of higher dimensional genetic networks are understandable on the hypercube. We have obtained the resultant output matrix based on the linear fractional maps, which are indispensable to understanding the system’s behavior.

A Generalization of Gene Network Representation on the Hypercube