Application of graph colouring to biological networks

Application of graph colouring to biological networks.

The author explores the application of graph colouring to biological networks, specifically protein-protein interaction (PPI) networks. First, the author finds that given similar conditions (i.e. graph size, degree distribution and clustering), fewer colours are needed to colour disassortative than assortative networks. Fewer colours create fewer independent sets which in turn imply higher conc...

Exploring biological networks with Graph Investigator research application

This paper describes Graph Investigator, the application intended for analysis of biological networks. A rich set of application functions is briefly described including graph feature generation, comparison, visualization and edition. The program enables to analyze global and local structural properties of networks with the use of various descriptors derived from graph theory. Furthermore, it a...

A grouping hyper-heuristic framework: Application on graph colouring

Grouping problems are hard to solve combinatorial optimisation problems which require partitioning of objects into a minimum number of subsets while a given objective is simultaneously optimized. Selection hyper-heuristics are high level general purpose search methodologies that operate on a space formed by a set of low level heuristics rather than solutions. Most of the recently proposed selec...

Colouring a Graph Frugally

Evolutionary Graph Colouring

The problem we are addressing in this paper was proposed at SIROCCO’98 by Kranakis [1], with possible applications to finding a consensus in distributive networks. The problem can be viewed as a simple game on graphs, in a way similar to the game of life. The aim is to colour all vertices of a graph, which are initially coloured with three colours 0,1, and 2, with a single colour. The only rule...