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Filtros : "Boareto, Marcelo" Limpar

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  • Artigo de periodico

    Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets (2015)

    Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B. P.; Alfonso, Nestor Felipe Caticha

    Source: IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS. Unidade: IF

    Subjects: ENTROPIA, RESSONÂNCIA MAGNÉTICA

    Versão PublicadaAcesso à fonteAcesso à fonteDOIHow to cite
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    • ABNT

      BOARETO, Marcelo et al. Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, v. 12, n. mai-ju 2015, p. 705-711, 2015Tradução . . Disponível em: https://doi.org/10.1109/tcbb.2014.2377750. Acesso em: 08 jun. 2024.

    • APA

      Boareto, M., Cesar, J., Leite, V. B. P., & Alfonso, N. F. C. (2015). Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 12( mai-ju 2015), 705-711. doi:10.1109/tcbb.2014.2377750

    • NLM

      Boareto M, Cesar J, Leite VBP, Alfonso NFC. Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets [Internet]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS. 2015 ; 12( mai-ju 2015): 705-711.[citado 2024 jun. 08 ] Available from: https://doi.org/10.1109/tcbb.2014.2377750

    • Vancouver

      Boareto M, Cesar J, Leite VBP, Alfonso NFC. Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets [Internet]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS. 2015 ; 12( mai-ju 2015): 705-711.[citado 2024 jun. 08 ] Available from: https://doi.org/10.1109/tcbb.2014.2377750

  • Artigo de periodico

    Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction (2012)

    Boareto, Marcelo; Yamagishi, Michel E B; Leite, Vitor B P; Caticha, Nestor

    Source: Computational Biology and Chemistry. Unidade: IF

    Subjects: ENZIMAS (ESTRUTURA), BIOINFORMÁTICA, FÍSICO-QUÍMICA

    Versão PublicadaAcesso à fonteAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      BOARETO, Marcelo et al. Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction. Computational Biology and Chemistry, v. 40, p. 15-19, 2012Tradução . . Disponível em: https://doi.org/10.1016/j.compbiolchem.2012.06.003. Acesso em: 08 jun. 2024.

    • APA

      Boareto, M., Yamagishi, M. E. B., Leite, V. B. P., & Caticha, N. (2012). Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction. Computational Biology and Chemistry, 40, 15-19. doi:10.1016/j.compbiolchem.2012.06.003

    • NLM

      Boareto M, Yamagishi MEB, Leite VBP, Caticha N. Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction [Internet]. Computational Biology and Chemistry. 2012 ;40 15-19.[citado 2024 jun. 08 ] Available from: https://doi.org/10.1016/j.compbiolchem.2012.06.003

    • Vancouver

      Boareto M, Yamagishi MEB, Leite VBP, Caticha N. Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction [Internet]. Computational Biology and Chemistry. 2012 ;40 15-19.[citado 2024 jun. 08 ] Available from: https://doi.org/10.1016/j.compbiolchem.2012.06.003
  • 1

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