Cluster analysis and artificial neural network on the superovulatory response prediction in mice

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dc.contributor.authorBrianezi, Gabriela Berni [UNESP]
dc.contributor.authorFrei, Fernando [UNESP]
dc.contributor.authorRocha, José Celso [UNESP]
dc.contributor.authorNogueira, Marcelo Fábio Gouveia [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:26:50Z
dc.date.available2014-05-27T11:26:50Z
dc.date.issued2012-06-13
dc.description.abstractComplex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.en
dc.description.affiliationDepartment of Biological Sciences College of Sciences and Letters São Paulo State University (UNESP) Campus Assis, Av Dom Antonio 2100, Vila Tenis Clube, CEP 19806900, Assis, São Paulo
dc.description.affiliationUnespDepartment of Biological Sciences College of Sciences and Letters São Paulo State University (UNESP) Campus Assis, Av Dom Antonio 2100, Vila Tenis Clube, CEP 19806900, Assis, São Paulo
dc.format.extent79-84
dc.identifierhttp://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0003876600790084
dc.identifier.citationProceedings of the International Workshop on Veterinary Biosignals and Biodevices, VBB 2012, in Conjunction with BIOSTEC 2012, p. 79-84.
dc.identifier.lattes4165274708509804
dc.identifier.lattes3734933152414412
dc.identifier.scopus2-s2.0-84861974536
dc.identifier.urihttp://hdl.handle.net/11449/73379
dc.language.isoeng
dc.relation.ispartofProceedings of the International Workshop on Veterinary Biosignals and Biodevices, VBB 2012, in Conjunction with BIOSTEC 2012
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectComplex biological systems
dc.subjectMouse embryos
dc.subjectResponse prediction
dc.subjectCluster analysis
dc.subjectForecasting
dc.subjectNeural networks
dc.subjectMammals
dc.titleCluster analysis and artificial neural network on the superovulatory response prediction in miceen
dc.typeTrabalho apresentado em evento
unesp.author.lattes4165274708509804
unesp.author.lattes3734933152414412
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências e Letras, Assispt

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