An algorithm for automated layout of process description maps drawn in SBGN

• Published in: Bioinformatics Vol. 32; no. 1; pp. 77 - 84
• Main Authors: Genc, Begum, Dogrusoz, Ugur
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.01.2016
• Subjects: Algorithms; Aspirin - pharmacology; Automation; Bioinformatics; Biological; Heuristics; Molecular structure; Original Papers; Pathways; Signal Transduction - drug effects; Systems Biology - methods; Vitamin B 6 - pharmacology
• ISSN: 1367-4803; 1367-4811; 1367-4811; 1460-2059
• DOI: 10.1093/bioinformatics/btv516

Motivation: Evolving technology has increased the focus on genomics. The combination of today’s advanced techniques with decades of molecular biology research has yielded huge amounts of pathway data. A standard, named the Systems Biology Graphical Notation (SBGN), was recently introduced to allow scientists to represent biological pathways in an unambiguous, easy-to-understand and efficient manner. Although there are a number of automated layout algorithms for various types of biological networks, currently none specialize on process description (PD) maps as defined by SBGN. Results: We propose a new automated layout algorithm for PD maps drawn in SBGN. Our algorithm is based on a force-directed automated layout algorithm called Compound Spring Embedder (CoSE). On top of the existing force scheme, additional heuristics employing new types of forces and movement rules are defined to address SBGN-specific rules. Our algorithm is the only automatic layout algorithm that properly addresses all SBGN rules for drawing PD maps, including placement of substrates and products of process nodes on opposite sides, compact tiling of members of molecular complexes and extensively making use of nested structures (compound nodes) to properly draw cellular locations and molecular complex structures. As demonstrated experimentally, the algorithm results in significant improvements over use of a generic layout algorithm such as CoSE in addressing SBGN rules on top of commonly accepted graph drawing criteria. Availability and implementation: An implementation of our algorithm in Java is available within ChiLay library (https://github.com/iVis-at-Bilkent/chilay). Contact:  ugur@cs.bilkent.edu.tr or dogrusoz@cbio.mskcc.org Supplementary information:  Supplementary data are available at Bioinformatics online.