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EpiGeNet

The EpiGeNet framework is a graph database for storage and querying of conditional relationships between molecular (genetic and epigenetic) events observed at different stages of colorectal (CRC) oncogenesis. Data were i) extracted from StatEpigen, a manually curated and annotated database, containing information on interdependencies between genetic and epigenetic signals, and specialized currently for CRC research, and ii) imported to our newly-developed EpiGeNet, which offers improved capability for management and visualization of data on molecular events specific to CRC initiation and progression.

How to access the EpiGeNet Framework

The EpiGeNet Framework can be accessed online here.

A non-exhaustive file with Cypher query examples for the EpiGeNet Framework is available for download here.

For developers

The EpiGeNet Framework is freely available for non-commercial purposes and the java code used for data integration and mapping into the framework 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

The executable jar can be directly downloaded from the Release page.

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

Balaur I., Saqi M., Barat A., Lysenko A., Mazein A., Rawlings C.J., Ruskin H.J. and Auffray, C. (2017), EpiGeNet: A Graph Database of Interdependencies Between Genetic and Epigenetic Events in Colorectal Cancer, Journal of Computational Biology. DOI: https://doi.org/10.1089/cmb.2016.0095.

Contributors

Irina Balaur, EISBM, Lyon, France - idea, specified the translation rules, developed the code

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

Ana Barat, [RCSI](https://www.rcsi.com/dublin/], Dublin, Ireland - advice on the input dataset

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

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

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

Heather J. Ruskin [Dublin City University], Dublin, Ireland - advice on the input dataset and on the translation rules

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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