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Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.

dc.contributor.authorPagano-Marquez, Raquel
dc.contributor.authorCordoba-Caballero, Jose
dc.contributor.authorMartinez-Poveda, Beatriz
dc.contributor.authorQuesada, Ana R
dc.contributor.authorRojano, Elena
dc.contributor.authorSeoane, Pedro
dc.contributor.authorRanea, Juan A G
dc.contributor.authorAngel Medina, Miguel
dc.contributor.funderSpanish Ministry of Science, Innovation and Universities
dc.contributor.funderAndalusian Government and FEDER
dc.date.accessioned2023-05-03T13:27:09Z
dc.date.available2023-05-03T13:27:09Z
dc.date.issued2022-07-18
dc.description.abstractAngiogenesis is regulated by multiple genes whose variants can lead to different disorders. Among them, rare diseases are a heterogeneous group of pathologies, most of them genetic, whose information may be of interest to determine the still unknown genetic and molecular causes of other diseases. In this work, we use the information on rare diseases dependent on angiogenesis to investigate the genes that are associated with this biological process and to determine if there are interactions between the genes involved in its deregulation. We propose a systemic approach supported by the use of pathological phenotypes to group diseases by semantic similarity. We grouped 158 angiogenesis-related rare diseases in 18 clusters based on their phenotypes. Of them, 16 clusters had traceable gene connections in a high-quality interaction network. These disease clusters are associated with 130 different genes. We searched for genes associated with angiogenesis througth ClinVar pathogenic variants. Of the seven retrieved genes, our system confirms six of them. Furthermore, it allowed us to identify common affected functions among these disease clusters. https://github.com/ElenaRojano/angio_cluster. seoanezonjic@uma.es and elenarojano@uma.es.
dc.description.versionSi
dc.identifier.citationPagano-Márquez R, Córdoba-Caballero J, Martínez-Poveda B, Quesada AR, Rojano E, Seoane P, et al. Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis. Brief Bioinform. 2022 Jul 18;23(4):bbac220.
dc.identifier.doi10.1093/bib/bbac220
dc.identifier.essn1477-4054
dc.identifier.pmcPMC9294413
dc.identifier.pmid35731990
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294413/pdf
dc.identifier.unpaywallURLhttps://academic.oup.com/bib/article-pdf/23/4/bbac220/45017071/bbac220.pdf
dc.identifier.urihttp://hdl.handle.net/10668/19705
dc.issue.number4
dc.journal.titleBriefings in bioinformatics
dc.journal.titleabbreviationBrief Bioinform
dc.language.isoen
dc.organizationInstituto de Investigación Biomédica de Málaga-IBIMA
dc.page.number15
dc.provenanceRealizada la curación de contenido 02/09/2025.
dc.publisherOxford University Press
dc.pubmedtypeJournal Article
dc.pubmedtypeResearch Support, Non-U.S. Gov't
dc.relation.projectIDPID2019-105010RB-I00
dc.relation.projectIDPID2019-108096RB-C21
dc.relation.projectIDUMA18-FEDERJA-102
dc.relation.projectIDUMA18-FEDERJA-220
dc.relation.projectIDPY20_00257
dc.relation.projectIDPY20_00372
dc.relation.projectIDRH-0079-2021
dc.relation.projectIDPAIDI BIO 267
dc.relation.publisherversionhttps://academic.oup.com/bib/article-lookup/doi/10.1093/bib/bbac220
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectangiogenesis
dc.subjectdisease clustering
dc.subjectrare diseases
dc.subjectsemantic similarity
dc.subjectsystems biology
dc.subjectCentro Andaluz de Nanomedicina y Biotecnología (BIONAND)
dc.subject.decsPlomo
dc.subject.decsPatología
dc.subject.decsEnfermedad
dc.subject.decsAdministración sistémica
dc.subject.decsFenotipo
dc.subject.decsSemántica
dc.subject.decsEnfermedades raras
dc.subject.decsAngiogénesis
dc.subject.meshAlgorithms
dc.subject.meshCluster Analysis
dc.subject.meshComputational Biology
dc.subject.meshHumans
dc.subject.meshPhenotype
dc.subject.meshRare Diseases
dc.subject.meshSemantics
dc.titleDeepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number23
dspace.entity.typePublication

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