StonPy: a tool to parse and query collections of SBGN maps in a graph database

Author:

Rougny Adrien12ORCID,Balaur Irina3,Luna Augustin45,Mazein Alexander3

Affiliation:

1. Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST) , Tokyo 135-0064, Japan

2. Com. Bio Big Data Open Innovation Lab. (CBBD-OIL), AIST , Tokyo 169-8555, Japan

3. Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7, avenue des Hauts Fourneaux , Esch-sur-Alzette L-4362, Luxembourg

4. Department of Systems Biology, Harvard Medical School , Boston, MA, USA

5. Department of Data Science, Dana-Farber Cancer Institute , Boston, MA, USA

Abstract

AbstractSummaryThe systems biology graphical notation (SBGN) has become the de facto standard for the graphical representation of molecular maps. Having rapid and easy access to the content of large collections of maps is necessary to perform semantic or graph-based analysis of these resources. To this end, we propose StonPy, a new tool to store and query SBGN maps in a Neo4j graph database. StonPy notably includes a data model that takes into account all three SBGN languages and a completion module to automatically build valid SBGN maps from query results. StonPy is built as a library that can be integrated into other software and offers a command-line interface that allows users to easily perform all operations.Availability and implementationStonPy is implemented in Python 3 under a GPLv3 license. Its code and complete documentation are freely available from https://github.com/adrienrougny/stonpy.Supplementary informationSupplementary data are available at Bioinformatics online.

Funder

University of Luxembourg

National Institute of General Medical Sciences

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference14 articles.

1. Systems biology graphical notation markup language (SBGNML) version 0.3;Bergmann;J. Integr. Bioinform,2020

2. Reactome graph database: efficient access to complex pathway data;Fabregat;PLoS Comput. Biol,2018

3. Atlas of cancer signalling network: a systems biology resource for integrative analysis of cancer data with google maps;Kuperstein;Oncogenesis,2015

4. The systems biology graphical notation;Le Novere;Nat. Biotechnol,2009

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