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Arenas-Galnares R, Castillo-Lara S, Toulis V, Boloc D, Gonzàlez-Duarte R, Marfany G, Abril JF. RPGeNet v2.0: expanding the universe of retinal disease gene interactions network. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2019:5618821. [PMID: 31712826 PMCID: PMC6846243 DOI: 10.1093/database/baz120] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 09/09/2019] [Accepted: 09/13/2019] [Indexed: 01/10/2023]
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.
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Affiliation(s)
- Rodrigo Arenas-Galnares
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Catalonia, Spain.,Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, 08028, Catalonia, Spain
| | - Sergio Castillo-Lara
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Catalonia, Spain.,Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, 08028, Catalonia, Spain
| | - Vasileios Toulis
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Catalonia, Spain.,Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, 08028, Catalonia, Spain.,CIBERER, ISCIII, University of Barcelona, Barcelona, 08028, Catalonia, Spain
| | - Daniel Boloc
- Faculty of Medicine, University of Barcelona, Barcelona, 08036, Catalonia, Spain
| | | | - Gemma Marfany
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Catalonia, Spain.,Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, 08028, Catalonia, Spain.,CIBERER, ISCIII, University of Barcelona, Barcelona, 08028, Catalonia, Spain.,DBGen Ocular Genomics, Barcelona, 08028, Catalonia, Spain
| | - Josep F Abril
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, 08028, Catalonia, Spain.,Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, 08028, Catalonia, Spain
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Castillo-Lara S, Abril JF. PPaxe: easy extraction of protein occurrence and interactions from the scientific literature. Bioinformatics 2019; 35:2523-2524. [PMID: 30500875 DOI: 10.1093/bioinformatics/bty988] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 10/26/2018] [Accepted: 11/29/2018] [Indexed: 11/15/2022] Open
Abstract
MOTIVATION Protein-protein interactions (PPIs) are very important to build models for understanding many biological processes. Although several databases hold many of these interactions, exploring them, selecting those relevant for a given subject and contextualizing them can be a difficult task for researchers. Extracting PPIs directly from the scientific literature can be very helpful for providing such context, as the sentences describing these interactions may give insights to researchers in helpful ways. RESULTS We have developed PPaxe, a python module and a web application that allows users to extract PPIs and protein occurrence from a given set of PubMed and PubMedCentral articles. It presents the results of the analysis in different ways to help researchers export, filter and analyze the results easily. AVAILABILITY AND IMPLEMENTATION PPaxe web demo is freely available at https://compgen.bio.ub.edu/PPaxe. All the software can be downloaded from https://compgen.bio.ub.edu/PPaxe/download, including a command-line version and docker containers for an easy installation. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Lázaro-Guevara J, Flores-Robles B, Garrido K, Pinillos-Aransay V, Elena-Ibáñez A, Merino-Meléndez L, López-Martínez J, Victoriano-Lacalle R. Gene's hubs in retinal diseases: A retinal disease network. Heliyon 2018; 4:e00867. [PMID: 30417144 PMCID: PMC6218668 DOI: 10.1016/j.heliyon.2018.e00867] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 06/28/2018] [Accepted: 10/11/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Retinal diseases associated with the dysfunction or death of photoreceptors are a major cause of blindness around the world, improvements in genetics tools, like next generation sequencing (NGS) allows the discovery of genes and genetic changes that lead to many of those retinal diseases. Though, there very few databases that explores a wide spectrum of retinal diseases, phenotypes, genes, and proteins, thus creating the need for a more comprehensive database, that groups all these parameters. METHODS Multiple open access databases were compiled into a new comprehensive database. A biological network was then crated, and organized using Cytoscape. The network was scrutinized for presence of hubs, measuring the concentration of grouped nodes. Finally, a trace back analysis was performed in areas were the power law reports a high r-squared value near one, that indicates high nodes density. RESULTS This work leads to creation of a retinal database that includes 324 diseases, 803 genes, 463 phenotypes, and 2461 proteins. Four biological networks (1) a disease and gene network connected by common phenotypes, (2) a disease and phenotype network connected by common genes, (3) a disease and gene network with shared disease or gene as the cause of an edge, and (4) a protein and disease network. The resulting networks will allow users to have easier searching for retinal diseases, phenotypes, genes, and proteins and their interrelationships. CONCLUSIONS These networks have a broader range of information than previously available ones, helping clinicians in the comprehension of this complex group of diseases.
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Affiliation(s)
| | | | - K. Garrido
- Paediatrics Department Guatemalan Social Secure Guatemala, Guatemala
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