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  • Artigo de periodico

    The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping (2024)

    Mello, Fábio Nunes de ; Tahira, Ana C ; Coelho, Maria Gabriela Berzoti ; Verjovski-Almeida, Sergio

    Source: Briefings in Bioinformatics. Unidade: IQ

    Subjects: ENTROPIA, GENOMAS

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

    • ABNT

      MELLO, Fábio Nunes de et al. The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping. Briefings in Bioinformatics, v. 25, n. 2, p. 1–15, 2024Tradução . . Disponível em: https://dx.doi.org/10.1093/bib/bbad538. Acesso em: 16 jun. 2025.

    • APA

      Mello, F. N. de, Tahira, A. C., Coelho, M. G. B., & Verjovski-Almeida, S. (2024). The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping. Briefings in Bioinformatics, 25( 2), 1–15. doi:10.1093/bib/bbad538

    • NLM

      Mello FN de, Tahira AC, Coelho MGB, Verjovski-Almeida S. The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping [Internet]. Briefings in Bioinformatics. 2024 ; 25( 2): 1–15.[citado 2025 jun. 16 ] Available from: https://dx.doi.org/10.1093/bib/bbad538

    • Vancouver

      Mello FN de, Tahira AC, Coelho MGB, Verjovski-Almeida S. The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping [Internet]. Briefings in Bioinformatics. 2024 ; 25( 2): 1–15.[citado 2025 jun. 16 ] Available from: https://dx.doi.org/10.1093/bib/bbad538

  • Artigo de periodico

    CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts (2021)

    Nachtigall, Pedro Gabriel ; Kashiwabara, André Yoshiaki ; Durham, Alan Mitchell

    Source: Briefings in Bioinformatics. Unidade: IME

    Subjects: BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO

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

    • ABNT

      NACHTIGALL, Pedro Gabriel e KASHIWABARA, André Yoshiaki e DURHAM, Alan Mitchell. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, v. 22, n. 3, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbaa045. Acesso em: 16 jun. 2025.

    • APA

      Nachtigall, P. G., Kashiwabara, A. Y., & Durham, A. M. (2021). CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, 22( 3), 1-11. doi:10.1093/bib/bbaa045

    • NLM

      Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1093/bib/bbaa045

    • Vancouver

      Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1093/bib/bbaa045

  • Artigo de periodico

    TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes (2021)

    Oliveira, Mauro de Medeiros ; Bonadio, Ígor ; Melo, Alícia Lie de ; Souza, Gláucia Mendes ; Durham, Alan Mitchell

    Source: Briefings in Bioinformatics. Unidades: IQ, IME, Interunidades em Bioinformática

    Subjects: TRANSCRIÇÃO GÊNICA, BIOINFORMÁTICA

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      OLIVEIRA, Mauro de Medeiros et al. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes. Briefings in Bioinformatics, v. 22, n. 6, p. 1-12, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbab198. Acesso em: 16 jun. 2025.

    • APA

      Oliveira, M. de M., Bonadio, Í., Melo, A. L. de, Souza, G. M., & Durham, A. M. (2021). TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes. Briefings in Bioinformatics, 22( 6), 1-12. doi:10.1093/bib/bbab198

    • NLM

      Oliveira M de M, Bonadio Í, Melo AL de, Souza GM, Durham AM. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes [Internet]. Briefings in Bioinformatics. 2021 ; 22( 6): 1-12.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1093/bib/bbab198

    • Vancouver

      Oliveira M de M, Bonadio Í, Melo AL de, Souza GM, Durham AM. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes [Internet]. Briefings in Bioinformatics. 2021 ; 22( 6): 1-12.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1093/bib/bbab198

  • Artigo de periodico

    A comparative study of statistical methods used to identify dependencies between gene expression signals (2014)

    Santos, Suzana de Siqueira ; Takahashi, Daniel Yasumasa ; Nakata, Asuka; Fujita, André

    Source: Briefings in Bioinformatics. Unidade: IME

    Subjects: BIOINFORMÁTICA, ESTATÍSTICA COMPUTACIONAL, CORRELAÇÃO GENÉTICA E AMBIENTAL

    Acesso à fonteDOIHow to cite
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    • ABNT

      SANTOS, Suzana de Siqueira et al. A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, v. 15, n. 6, p. 906-918, 2014Tradução . . Disponível em: https://doi.org/10.1093/bib/bbt051. Acesso em: 16 jun. 2025.

    • APA

      Santos, S. de S., Takahashi, D. Y., Nakata, A., & Fujita, A. (2014). A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, 15( 6), 906-918. doi:10.1093/bib/bbt051

    • NLM

      Santos S de S, Takahashi DY, Nakata A, Fujita A. A comparative study of statistical methods used to identify dependencies between gene expression signals [Internet]. Briefings in Bioinformatics. 2014 ; 15( 6): 906-918.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1093/bib/bbt051

    • Vancouver

      Santos S de S, Takahashi DY, Nakata A, Fujita A. A comparative study of statistical methods used to identify dependencies between gene expression signals [Internet]. Briefings in Bioinformatics. 2014 ; 15( 6): 906-918.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1093/bib/bbt051
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