Analysis of Boolean Functions based on Interaction Graphs and their influence in System Biology

TL;DR

This paper introduces a new method for constructing interaction graphs in systems biology using Boolean function decomposition, highlighting the significance of 2-bit decompositions for understanding gene and protein regulation.

Contribution

It presents a novel approach to build interaction graphs from Boolean functions, emphasizing the biological importance of specific Boolean function classes.

Findings

Different classes of Boolean functions with biological significance identified

Interaction graphs constructed via Boolean function decomposition

Enhanced understanding of gene and protein regulation mechanisms

Abstract

Interaction graphs provide an important qualitative modeling approach for System Biology. This paper presents a novel approach for construction of interaction graph with the help of Boolean function decomposition. Each decomposition part (Consisting of 2-bits) of the Boolean functions has some important significance. In the dynamics of a biological system, each variable or node is nothing but gene or protein. Their regulation has been explored in terms of interaction graphs which are generated by Boolean functions. In this paper, different classes of Boolean functions with regards to Interaction Graph with biologically significant properties have been adumbrated.