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dc.contributor.authorMorilla, Ian
dc.date.accessioned2018-09-17T10:34:09Z
dc.date.available2018-09-17T10:34:09Z
dc.date.created2018
dc.date.issued2018-09-17
dc.identifier.urihttps://hdl.handle.net/10630/16478
dc.description.abstractIn Biology, genes interactions are usually described in terms of graphs. Certain of those genes dispose in bi-functional modules within the graph according to their (anti)correlation to a state of functioning (e.g., permittivity to a genetic disorder of codominant traits). A disease may be characterised by a finite number of those modules. For a given module, there exist some allelic variants at risk (i.e., genetics risk factor) leading to a permissive state what eventually would cause disease in an individual if the other modules were also in the same permissive state. At present, the effective modelling of all these inherited genetics factors is impossible in biomedicine. However, within the framework of evolution algebras, it can be possible. In this work, we will explore connections between random walks on disease graphs and the evolution algebra determined by the same graph.en_US
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGenéticaen_US
dc.subjectGenesen_US
dc.subjectCiencias biomédicasen_US
dc.subject.otherBiomedicinaen_US
dc.titleConnections between evolution algebras and graphical model of hereditary diseaseen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.centroEscuela de Ingenierías Industrialesen_US
dc.relation.eventtitleResearch School on Evolution Algebras and Non Associative Algebraic Structures.en_US
dc.relation.eventplaceEscuela de Ingenierías Industrialesen_US
dc.relation.eventdate15,16 y 17 de Octurbre del 2018en_US


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