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

BMC Bioinformatics

Software

Dagmar Waltemath¹  Vasundra Touré²  Alexander Mazein³  Irina Balaur³  Johann Pellet³  Mansoor Saqi³  Charles Auffray³  Ron Henkel⁴ 

[1] Department of Systems Biology and Bioinformatics, University of Rostock, 18051, Rostock, Germany;Department of Systems Biology and Bioinformatics, University of Rostock, 18051, Rostock, Germany;European Institute for Systems Biology and Medicine (EISBM), CIRI UMR 5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007, Lyon, France;European Institute for Systems Biology and Medicine (EISBM), CIRI UMR 5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007, Lyon, France;Scientific Databases and Visualization, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany;Department of Business Information Systems, University of Rostock, 18051, Rostock, Germany;

关键词: Systems biology graphical notation;    Neo4j;    Graph database;    Systems biology;    Systems medicine;   

DOI  :  10.1186/s12859-016-1394-x

 received in 2016-05-04, accepted in 2016-11-29,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundWhen 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.ResultsWe 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.ConclusionSTON 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.

【 授权许可】

CC BY   
© The Author(s) 2016