Learning to capture the functions of genetic regulatory networks using graph motifs

Abstract

Network motifs have been suggested as a means to understand Systems biological functions. Based on several arguments from computer science, logic, mathematics, chemistry and non-linear dynamics, we explain the difficulties encountered in capturing the evolving dynamical functions carried out by the genetic regulatory networks (GRN), based on the assembly of motifs. Show more