STON: exploring biological pathways using the SBGN standard and graph databases

BMC Bioinformatics. 2016 Dec 5;17(1):494. doi: 10.1186/s12859-016-1394-x.

Abstract

Background: When modeling in Systems Biology and Systems Medicine, the data is often extensive, complex and heterogeneous. Graphs are a natural way of representing biological networks. Graph databases enable efficient storage and processing of the encoded biological relationships. They furthermore support queries on the structure of biological networks.

Results: We present the Java-based framework STON (SBGN TO Neo4j). STON imports and translates metabolic, signalling and gene regulatory pathways represented in the Systems Biology Graphical Notation into a graph-oriented format compatible with the Neo4j graph database.

Conclusion: STON exploits the power of graph databases to store and query complex biological pathways. This advances the possibility of: i) identifying subnetworks in a given pathway; ii) linking networks across different levels of granularity to address difficulties related to incomplete knowledge representation at single level; and iii) identifying common patterns between pathways in the database.

Keywords: Graph database; Neo4j; Systems biology; Systems biology graphical notation; Systems medicine.

MeSH terms

  • Databases, Factual
  • Gene Regulatory Networks*
  • Humans
  • Metabolic Networks and Pathways*
  • Signal Transduction*
  • Software*
  • Systems Biology / methods*