EpiGeNet : A graph database of interdependencies between genetic and epigenetic events in colorectal cancer

A - Papers appearing in refereed journals

Balaur, I., Saqi, M., Barat, A., Lysenko, A., Mazein, A., Ruskin, H. J., Auffray, C. and Rawlings, C. J. 2017. EpiGeNet : A graph database of interdependencies between genetic and epigenetic events in colorectal cancer. Journal of Computational Biology. 24 (10), pp. 969-980. https://doi.org/10.1089/cmb.2016.0095

AuthorsBalaur, I., Saqi, M., Barat, A., Lysenko, A., Mazein, A., Ruskin, H. J., Auffray, C. and Rawlings, C. J.
Abstract

The development of colorectal cancer (CRC)—the third most common cancer type—has been associated with deregulations of cellular mechanisms stimulated by both genetic and epigenetic events. StatEpigen is a manually curated and annotated database, containing information on interdependencies between genetic and epigenetic signals, and specialized currently for CRC research. Although StatEpigen provides a well-developed graphical user interface for information retrieval, advanced queries involving associations between multiple concepts can benefit from more detailed graph representation of the integrated data. This can be achieved by using a graph database (NoSQL) approach. Data were extracted from StatEpigen and imported to our newly developed EpiGeNet, a graph database for storage and querying of conditional relationships between molecular (genetic and epigenetic) events observed at different stages of colorectal oncogenesis. We illustrate the enhanced capability of EpiGeNet for exploration of different queries related to colorectal tumor progression; specifically, we demonstrate the query process for (i) stage-specific molecular events, (ii) most frequently observed genetic and epigenetic interdependencies in colon adenoma, and (iii) paths connecting key genes reported in CRC and associated events. The EpiGeNet framework offers improved capability for management and visualization of data on molecular events specific to CRC initiation and progression.

Year of Publication2017
JournalJournal of Computational Biology
Journal citation24 (10), pp. 969-980
Digital Object Identifier (DOI)https://doi.org/10.1089/cmb.2016.0095
PubMed ID27627442
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeFrom data to knowledge / the ONDEX System for integrating Life Sciences data sources
Publisher's version
Output statusPublished
Publication dates
Online14 Sep 2016
Copyright licenseCC BY
PublisherMary Ann Liebert, Inc
ISSN1066-5277

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