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dc.contributor.authorMarín, Milagros
dc.contributor.authorEsteban, Francisco
dc.contributor.authorRamírez Rodrigo, Hilario 
dc.contributor.authorRos Vidal, Eduardo 
dc.contributor.authorSáez Lara, María José 
dc.date.accessioned2019-12-12T10:42:03Z
dc.date.available2019-12-12T10:42:03Z
dc.date.issued2019
dc.identifier.citationMarín, M., Esteban, F. J., Ramírez-Rodrigo, H., Ros, E., & Sáez-Lara, M. J. (2019). An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies. BMC bioinformatics, 20(1), 1-13.es_ES
dc.identifier.urihttp://hdl.handle.net/10481/58271
dc.description.abstractBiologically data-driven networks have become powerful analytical tools that handle massive, heterogeneous datasets generated from biomedical fields. Protein-protein interaction networks can identify the most relevant structures directly tied to biological functions. Functional enrichments can then be performed based on these structural aspects of gene relationships for the study of channelopathies. Channelopathies refer to a complex group of disorders resulting from dysfunctional ion channels with distinct polygenic manifestations. This study presents a semi-automatic workflow using protein-protein interaction networks that can identify the most relevant genes and their biological processes and pathways in channelopathies to better understand their etiopathogenesis. In addition, the clinical manifestations that are strongly associated with these genes are also identified as the most characteristic in this complex group of diseases. This research provides a systems biology approach to extract information from interaction networks of gene expression. We show how large-scale computational integration of heterogeneous datasets, PPI network analyses, functional databases and published literature may support the detection and assessment of possible potential therapeutic targets in the disease. Applying our workflow makes it feasible to spot the most relevant genes and unknown relationships in channelopathies and shows its potential as a first-step approach to identify both genes and functional interactions in clinical-knowledge scenarios of target diseases.es_ES
dc.description.sponsorshipThis work was supported by funds from MINECO-FEDER (TIN2016–81041-R to E.R.), European Human Brain Project SGA2 (H2020-RIA 785907 to M.J.S.), Junta de Andalucía (BIO-302 to F.J.E.) and MEIC (Systems Medicine Excellence Network, SAF2015–70270-REDT to F.J.E.).es_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectChannelopathieses_ES
dc.subjectProtein-protein interaction networkses_ES
dc.subjectBehavioural diagnosises_ES
dc.subjectGenetic diseaseses_ES
dc.subjectSystems medicinees_ES
dc.titleAn integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1186/s12859-019-3162-1


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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España