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dc.contributor.authorVázquez-Prieto S.
dc.contributor.authorPaniagua E.
dc.contributor.authorSolana H.
dc.contributor.authorUbeira F.M.
dc.date.accessioned2020-09-02T22:30:31Z
dc.date.available2020-09-02T22:30:31Z
dc.date.issued2017
dc.identifier10.2174/1568026618666171211150605
dc.identifier.citation17, 30, 3249-3255
dc.identifier.issn15680266
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6620
dc.descriptionBackground: Complex network approach allows the representation and analysis of complex systems of interacting agents in an ordered and effective manner, thus increasing the probability of discovering significant properties of them. In the present study, we defined and built for the first time a complex network based on data obtained from Immune Epitope Database for parasitic organisms. We then considered the general topology, the node degree distribution, and the local structure (triadic census) of this network. In addition, we calculated 9 node centrality measures for observed network and reported a comparative study of the real network with three theoretical models to detect similarities or deviations from these ideal networks. Result: The results obtained corroborate the utility of the complex network approach for handling information and data mining within the database under study. Conclusion: They confirm that this type of approach can be considered a valuable tool for preliminary screening of the best experimental conditions to determine whether the amino acid sequences being studied are true epitopes or not. © 2017 Bentham Science Publishers.
dc.language.isoen
dc.publisherBentham Science Publishers B.V.
dc.subjectB-cells epitopes
dc.subjectImmune epitope database
dc.subjectNetwork theory
dc.subjectParasitic organisms
dc.subjectTopological indices
dc.subjectTopological indices
dc.subjectepitope
dc.subjectepitope
dc.subjectamino acid sequence
dc.subjectArticle
dc.subjectbioinformatics
dc.subjectcomparative study
dc.subjectcomplex network approach
dc.subjectdata analysis
dc.subjectdata mining
dc.subjectfactual database
dc.subjectinformation processing
dc.subjectmathematical analysis
dc.subjectnonhuman
dc.subjectparasite
dc.subjectsystem analysis
dc.subjecttheoretical model
dc.subjectanimal
dc.subjectartificial neural network
dc.subjectchemistry
dc.subjectimmunology
dc.subjectparasite
dc.subjectAmino Acid Sequence
dc.subjectAnimals
dc.subjectData Mining
dc.subjectDatabases, Factual
dc.subjectEpitopes
dc.subjectNeural Networks (Computer)
dc.subjectParasites
dc.titleComplex network study of the immune epitope database for parasitic organisms
dc.typeArticle


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