Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/814
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorOLIVEIRA, S. R. de M.pt_BR
dc.contributor.authorALMEIDA, G. V.pt_BR
dc.contributor.authorSOUZA, K. R. R.pt_BR
dc.contributor.authorRODRIGUES, D. N.pt_BR
dc.contributor.authorKUSER-FALCÃO, P. R.pt_BR
dc.contributor.authorYAMAGISHI, M. E. B.pt_BR
dc.contributor.authorSANTOS, E. H. dospt_BR
dc.contributor.authorVIEIRA, F. D.pt_BR
dc.contributor.authorJARDINE, J. G.pt_BR
dc.contributor.authorNESHICH, G.pt_BR
dc.date.accessioned2011-04-10T11:11:11Zpt_BR
dc.date.available2011-04-10T11:11:11Zpt_BR
dc.date.created2007-12-07pt_BR
dc.date.issued2007pt_BR
dc.identifier.citationGenetics and Molecular Research, v. 6, n. 4, p. 911-922, 2007.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/814pt_BR
dc.descriptionAbstract. An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting_RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting_RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting_RDB toward data quality assessment. To the best of our knowledge, Sting_RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting_RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting_rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectBioinformáticapt_BR
dc.subjectAnálise de estrutura de proteínaspt_BR
dc.subjectMineração de dadospt_BR
dc.subjectBase de dados Stingpt_BR
dc.subjectData miningpt_BR
dc.subjectData warehousingpt_BR
dc.titleSting_RDB: a relational database of structural parameters for protein analysis with support for data warehousing and data mining.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2017-05-11T11:11:11Zpt_BR
dc.subject.thesagroProteínapt_BR
dc.subject.nalthesaurusBioinformaticspt_BR
dc.subject.nalthesaurusProteinspt_BR
dc.subject.nalthesaurusDatabasespt_BR
riaa.ainfo.id814pt_BR
riaa.ainfo.lastupdate2017-05-11pt_BR
dc.contributor.institutionSTANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; PAULA REGINA KUSER FALCAO, CNPTIA; MICHEL EDUARDO BELEZA YAMAGISHI, CNPTIA; EDGARD HENRIQUE DOS SANTOS, CNPTIA; FABIO DANILO VIEIRA, CNPTIA; JOSE GILBERTO JARDINE, CNPTIA; GORAN NESHICH, CNPTIA.pt_BR
Aparece nas coleções:Artigo em periódico indexado (CNPTIA)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
APStingGMR2007.pdf778,33 kBAdobe PDFThumbnail
Visualizar/Abrir
Mostrar registro simples do item Visualizar estatísticas

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace