Automatically layout and visualize the biological pathway map with spectral graph theory

TL;DR

This paper introduces an automated method for visualizing biological pathway maps using spectral graph theory and topological sorting, significantly improving readability by reducing edge crossings and node adjacency issues.

Contribution

It presents a novel automated approach for pathway map visualization that enhances clarity and reduces visual clutter compared to manual methods.

Findings

Significant reduction in edge crossings achieved

Improved readability of pathway maps

Automated visualization process based on spectral graph theory

Abstract

The pathway is a biological term that refers to a series of interactions between molecules in a cell that causes a certain product or a change in the cell. Pathway analysis is a powerful method for gene expression analysis. Through pathway maps, the lists of genes that are differentially expressed across the given phenotypes are translated into various biological phenomena. Visualizing a pathway map manually is a common practice nowadays because of the limitations of existing solutions to draw complicated graphs (i.e. directed graphs, graphs with edge crossings, etc). This project provides a solution to draw pathway maps automatically based on spectral graph theory and topological sort. Various methods are taken to enhance pathway maps' readability. Significant reductions in the number of edge crossings and the sum of adjacent nodes are achieved.