A generic algorithm for layout of biological networks

Falk Schreiber,Tim Dwyer,Kim Marriott,Michael Wybrow

doi:10.1186/1471-2105-10-375

Abstract

BackgroundBiological networks are widely used to represent processes in biological systems and to capture interactions and dependencies between biological entities. Their size and complexity is steadily increasing due to the ongoing growth of knowledge in the life sciences. To aid understanding of biological networks several algorithms for laying out and graphically representing networks and network analysis results have been developed. However, current algorithms are specialized to particular layout styles and therefore different algorithms are required for each kind of network and/or style of layout. This increases implementation effort and means that new algorithms must be developed for new layout styles. Furthermore, additional effort is necessary to compose different layout conventions in the same diagram. Also the user cannot usually customize the placement of nodes to tailor the layout to their particular need or task and there is little support for interactive network exploration.ResultsWe present a novel algorithm to visualize different biological networks and network analysis results in meaningful ways depending on network types and analysis outcome. Our method is based on constrained graph layout and we demonstrate how it can handle the drawing conventions used in biological networks.ConclusionThe presented algorithm offers the ability to produce many of the fundamental popular drawing styles while allowing the exibility of constraints to further tailor these layouts.

Highlights

Biological networks are widely used to represent processes in biological systems and to capture interactions and dependencies between biological entities
A significant contribution of this paper is to show that separation constraints, despite their apparent simplicity and their limitation to act on a single dimension can be used to encode the wide variety of specialized layout requirements arising in biological networks
Placement Constraints we show that our approach of dynamically generating separation constraints is very powerful and supports the kinds of placement constraints arising in biological networks

Summary

Introduction

Biological networks are widely used to represent processes in biological systems and to capture interactions and dependencies between biological entities. Their size and complexity is steadily increasing due to the ongoing growth of knowledge in the life sciences. Current algorithms are specialized to particular layout styles and different algorithms are required for each kind of network and/or style of layout This increases implementation effort and means that new algorithms must be developed for new layout styles. Networks play a central role in biological investigation of organisms They are used to represent processes in biological systems and to capture interactions and dependencies between biological entities such as genes, transcripts, proteins and metabolites. To tackle this complexity and help in analyzing and interpreting the complicated web of interactions meaningful visualizations of biological networks are crucial

Methods

Results

Conclusion