Publications

@article{Díaz-Montaña2019,

title = {Development and use of a Cytoscape app for GRNCOP2},

author = {J. J. Díaz-Montaña and N. Díaz-Díaz and C. D. Barranco and I. Ponzoni},

url = {http://www.sciencedirect.com/science/article/pii/S0169260718313592},

doi = {10.1016/j.cmpb.2019.05.030},

issn = {0169-2607},

year  = {2019},

date = {2019-08-01},

journal = {Computer Methods and Programs in Biomedicine},

volume = {177},

pages = {211-218},

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.



Availability: The GRNCOP2 App is freely available at the official Cytoscape app store: http://apps.cytoscape.org/apps/grncop2},

keywords = {Cytoscape},

pubstate = {published},

tppubtype = {article}

}

@article{Díaz-Montaña2018,

title = {GNC–app: A new Cytoscape app to rate gene networks biological coherence using gene–gene indirect relationships},

author = {J. J. Díaz-Montaña and F. Gómez-Vela and N. Díaz-Díaz},

url = {http://www.sciencedirect.com/science/article/pii/S0303264717303258},

doi = {10.1016/j.biosystems.2018.01.007},

issn = {0303-2647},

year  = {2018},

date = {2018-04-01},

journal = {Biosystems},

volume = {166},

pages = {61-65},

abstract = {Motivation

Gene networks are currently considered a powerful tool to model biological processes in the Bioinformatics field. A number of approaches to infer gene networks and various software tools to handle them in a visual simplified way have been developed recently. However, there is still a need to assess the inferred networks in order to prove their relevance.



Results

In this paper, we present the new GNC-app for Cytoscape. GNC-app implements the GNC methodology for assessing the biological coherence of gene association networks and integrates it into Cytoscape. Implemented de novo, GNC-app significantly improves the performance of the original algorithm in order to be able to analyse large gene networks more efficiently. It has also been integrated in Cytoscape to increase the tool accessibility for non-technical users and facilitate the visual analysis of the results. This integration allows the user to analyse not only the global biological coherence of the network, but also the biological coherence at the gene–gene relationship level. It also allows the user to leverage Cytoscape capabilities as well as its rich ecosystem of apps to perform further analyses and visualizations of the network using such data.



Availability

The GNC-app is freely available at the official Cytoscape app store: http://apps.cytoscape.org/apps/gnc.},

keywords = {Cytoscape, Gene Network},

pubstate = {published},

tppubtype = {article}

}