6533b81ffe1ef96bd12773b4

RESEARCH PRODUCT

Reactome graph database: Efficient access to complex pathway data

Henning HermjakobHenning HermjakobPablo Marin-garciaFlorian KorningerPeter D'eustachioPeipei PingLincoln SteinLincoln SteinGuanming WuGuilherme ViteriAntonio FabregatKonstantinos Sidiropoulos

subject

0301 basic medicineDatabases FactualComputer scienceData managementKnowledge BasesSocial SciencesInformation Storage and RetrievalNoSQLcomputer.software_genreComputer ApplicationsDatabase and Informatics MethodsUser-Computer Interface0302 clinical medicineKnowledge extractionPsychologyDatabase Searchinglcsh:QH301-705.5Data ManagementLanguageBiological dataEcologySystems BiologyGenomicsGenomic DatabasesComputational Theory and MathematicsModeling and SimulationWeb-Based ApplicationsGraph (abstract data type)Information TechnologyResearch ArticleComputer and Information SciencesRelational databaseQuery languageResearch and Analysis MethodsEcosystems03 medical and health sciencesCellular and Molecular NeuroscienceDatabasesGeneticsComputer GraphicsHumansMolecular BiologyEcology Evolution Behavior and SystematicsInternetInformation retrievalGraph databasebusiness.industryEcology and Environmental SciencesCognitive PsychologyBiology and Life SciencesComputational BiologyGenome AnalysisRelational Databases030104 developmental biologyBiological Databaseslcsh:Biology (General)Cognitive Sciencebusinesscomputer030217 neurology & neurosurgerySoftwareNeuroscience

description

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.

10.1371/journal.pcbi.1005968http://europepmc.org/articles/PMC5805351