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RPGeNet v2.0: expanding the universe of retinal disease gene interactions network.


ABSTRACT: RPGeNet offers researchers a user-friendly queriable tool to visualize the interactome network of visual disorder genes, thus enabling the identification of new potential causative genes and the assignment of novel candidates to specific retinal or cellular pathways. This can be highly relevant for clinical applications as retinal dystrophies affect 1:3000 people worldwide, and the causative genes are still unknown for 30% of the patients. RPGeNet is a refined interaction network interface that limits its skeleton network to the shortest paths between each and every known causative gene of inherited syndromic and non-syndromic retinal dystrophies. RPGeNet integrates interaction information from STRING, BioGRID and PPaxe, along with retina-specific expression data and associated genetic variants, over a Cytoscape.js web interface. For the new version, RPGeNet v2.0, the database engine was migrated to Neo4j graph database manager, which speeds up the initial queries and can handle whole interactome data for new ways to query the network. Further, user facilities have been introduced as the capability of saving and restoring a researcher customized network layout or as novel features to facilitate navigation and data projection on the network explorer interface. Responsiveness has been further improved by transferring some functionality to the client side.

SUBMITTER: Arenas-Galnares R 

PROVIDER: S-EPMC6846243 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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RPGeNet v2.0: expanding the universe of retinal disease gene interactions network.

Arenas-Galnares Rodrigo R   Castillo-Lara Sergio S   Toulis Vasileios V   Boloc Daniel D   Gonzàlez-Duarte Roser R   Marfany Gemma G   Abril Josep F JF  

Database : the journal of biological databases and curation 20190101


RPGeNet offers researchers a user-friendly queriable tool to visualize the interactome network of visual disorder genes, thus enabling the identification of new potential causative genes and the assignment of novel candidates to specific retinal or cellular pathways. This can be highly relevant for clinical applications as retinal dystrophies affect 1:3000 people worldwide, and the causative genes are still unknown for 30% of the patients. RPGeNet is a refined interaction network interface that  ...[more]

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