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dc.contributor.author
Díaz Montaña, Juan José
dc.contributor.author
Díaz Díaz, Norberto
dc.contributor.author
Barranco, Carlos D.
dc.contributor.author
Ponzoni, Ignacio
dc.date.available
2020-11-02T20:05:42Z
dc.date.issued
2019-08-04
dc.identifier.citation
Díaz Montaña, Juan José; Díaz Díaz, Norberto; Barranco, Carlos D.; Ponzoni, Ignacio; Development and use of a cytoscape app for GRNCOP2; Elsevier Ireland; Computer Methods And Programs In Biomedicine; 177; 4-8-2019; 211-218
dc.identifier.issn
0169-2607
dc.identifier.uri
http://hdl.handle.net/11336/117429
dc.description.abstract
Background and Objective: Gene regulatory networks (GRNs) are essential for understanding most molecular processes. In this context, the so-called model-free approaches have an advantage modeling the complex topologies behind these dynamic molecular networks, since most GRNs are difficult to map correctly by any other mathematical model. Abstract model-free approaches, also known as rule-based extraction methods, offer valuable benefits when performing data-driven analysis; such as requiring the least amount of data and simplifying the inference of large models at a faster analysis speed. In particular, GRNCOP2 is a combinatorial optimization method with an adaptive criterion for the discretization of gene expression data and high performance, in contrast to other rule-based extraction methods for discovering GRNs. However, the analysis of the large relational structures of the networks inferred by GRNCOP2 requires the support of effective tools for interactive network visualization and topological analysis of the extracted associations. This need motivated the possibility of integrating GRNCOP2 in the Cytoscape ecosystem in order to benefit from Cytoscapes core functionality, as well as all the other apps in its ecosystem. Methods: In this paper, we introduce the implementation of a GRNCOP2 Cytoscape app. This incorporation to Cytoscape platform includes new functionality for GRN visualizations, dynamic user-interaction and integration with other apps for topological analysis of the networks. Results: In order to demonstrate the usefulness of integrating GRNCOP2 in Cytoscape, the new app was used to tackle a novel use case for GRNCOP2: the analysis of crosstalk between pathways. In this regard, datasets associated with Alzheimer's disease (AD) were analyzed using GRNCOP2 app and other apps of the Cytoscape ecosystem by performing a topological analysis of the AD progression and its synchronization with the Ubiquitin Mediated Proteolysis pathway. Finally, the biological relevance of the findings achieved by this new app were evaluated by searching for evidence in the literature. Conclusions: The proposed crosstalk analysis with the new GRNCOP2 app focused on assessing the phase of the Alzheimer's disease progression where the coordination with the Ubiquitin Mediated Proteolysis pathway increase, and identifying the genes that explain the signalling between these cellular processes. Both questions were explored by topological contrastive analysis of the GRNs generated for the GRNCOP2 app, where several facilities of Cytoscape were exploited. The topological patterns inferred by this new App have been consistent with biological evidence reported in the scientic literature, illustrating the effectiveness of using this new GRNCOP2 App in pathway analysis.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Ireland
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
ALZHEIMER'S DISEASE
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CYTOSCAPE
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GENE REGULATORY NETWORKS
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MACHINE LEARNING
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PATHWAY CROSSTALK
dc.subject.classification
Ciencias de la Información y Bioinformática
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Development and use of a cytoscape app for GRNCOP2
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-02-26T19:39:28Z
dc.journal.volume
177
dc.journal.pagination
211-218
dc.journal.pais
Irlanda
dc.journal.ciudad
Shannon
dc.description.fil
Fil: Díaz Montaña, Juan José. Universidad Pablo de Olavide; España
dc.description.fil
Fil: Díaz Díaz, Norberto. Universidad Pablo de Olavide; España
dc.description.fil
Fil: Barranco, Carlos D.. Universidad Pablo de Olavide; España
dc.description.fil
Fil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
dc.journal.title
Computer Methods And Programs In Biomedicine
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0169260718313592
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.cmpb.2019.05.030
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