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The Protein Framework

The Protein Framework uses the Neo4j graph platform for the integration of multiple heterogeneous biological data sources (such as protein-protein interactions, pathways, drug-target interactions, disease-gene interactions, sequence similarity relationships). The integrated network allows the biological context of disease associated genes to be explored through visualisation, and information can be retrieved using the powerful neo4j CYPHER query language.

Tutorial available here.

How to access the Protein Framework

The Protein Framework addresses to several categories of users:

General user (knowledgebase manager):

The Protein Framework can be accessed online here.

A file with several Cypher query examples for the Protein Framework is available for download here. These queries can be extended to accommodate specific topics of interest.

Advanced biological queries:

For more advanced biological queries and/or further exploration of the results, the Protein Framework can be interrogated directly using java and R. An example of running a simple Cypher query in the Protein Framework using directly R code (via the RNeo4j library) is available here.

For developers

The Protein Framework is freely available for non-commercial purposes and the java code used to parse the data and populate the graph database is available here.

Requirements

  • Java 7
  • Maven (tested with Maven 3.5)

Install

After cloning the repository and getting into its directory:

mvn clean

mvn install

How to contribute

If you have any suggestions or want to report a bug, don't hesitate to create an issue. Pull requests and all forms of contribution will be warmly welcomed.

Please cite our paper on this work

Lysenko A., Roznovat I.A., Saqi M., Mazein A., Rawlings C.J. and Auffray C. (2016), Representing and querying disease networks using graph databases ( Contributed equally). BioData Mining, pp. 9:23. DOI: 10.1186/s13040-016-0102-8.

Contributors

Irina Balaur (Roznovat), EISBM, Lyon, France - specified the translation rules, developed the code

Artem Lysenko, Rothamsted Research, Hertfordshire, UK - advice on the Neo4j functionality

Alexander Mazein, EISBM, Lyon, France - idea, advice on the translation rules

Mansoor Saqi, EISBM, Lyon, France - advice on the translation rules

Chris J. Rawlings, Rothamsted Research, Hertfordshire, UK - advice on the Neo4j functionality

Charles Auffray, EISBM, Lyon, France - strategic advice

Useful links

Acknowledgements

This work has been supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. IMI 115446 (eTRIKS), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies.

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This framework is part of the DiseaseNetworks module, eTRIKS Lab

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