Fast grid layout algorithm for biological networks with sweep calculation

Bioinformatics. 2008 Jun 15;24(12):1433-41. doi: 10.1093/bioinformatics/btn196. Epub 2008 Apr 18.

Abstract

Motivation: Properly drawn biological networks are of great help in the comprehension of their characteristics. The quality of the layouts for retrieved biological networks is critical for pathway databases. However, since it is unrealistic to manually draw biological networks for every retrieval, automatic drawing algorithms are essential. Grid layout algorithms handle various biological properties such as aligning vertices having the same attributes and complicated positional constraints according to their subcellular localizations; thus, they succeed in providing biologically comprehensible layouts. However, existing grid layout algorithms are not suitable for real-time drawing, which is one of requisites for applications to pathway databases, due to their high-computational cost. In addition, they do not consider edge directions and their resulting layouts lack traceability for biochemical reactions and gene regulations, which are the most important features in biological networks.

Results: We devise a new calculation method termed sweep calculation and reduce the time complexity of the current grid layout algorithms through its encoding and decoding processes. We conduct practical experiments by using 95 pathway models of various sizes from TRANSPATH and show that our new grid layout algorithm is much faster than existing grid layout algorithms. For the cost function, we introduce a new component that penalizes undesirable edge directions to avoid the lack of traceability in pathways due to the differences in direction between in-edges and out-edges of each vertex.

Availability: Java implementations of our layout algorithms are available in Cell Illustrator.

Contact: masao@ims.u-tokyo.ac.jp

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Algorithms*
  • Computer Graphics*
  • Computer Simulation
  • Information Storage and Retrieval / methods
  • Models, Biological*
  • Proteome / metabolism*
  • Signal Transduction / physiology*
  • User-Computer Interface*

Substances

  • Proteome