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Filtros : "Journal of Bioinformatics and Computational Biology" Limpar

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  • Artigo de periodico

    A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification (2023)

    Relvas, Carlos E. M.; Nakata, Asuka; Chen, Guoan; Beer, David G. ; Gotoh, Noriko ; Fujita, André

    Source: Journal of Bioinformatics and Computational Biology. Unidade: IME

    Subjects: BIOINFORMÁTICA, NEOPLASIAS PULMONARES, MODELOS PARA PROCESSOS ESTOCÁSTICOS

    Versão PublicadaAcesso à fonteDOIHow to cite
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    • ABNT

      RELVAS, Carlos E. M. et al. A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification. Journal of Bioinformatics and Computational Biology, v. 21, n. artigo 2350019, p. 1-26, 2023Tradução . . Disponível em: https://doi.org/10.1142/S0219720023500191. Acesso em: 28 abr. 2024.

    • APA

      Relvas, C. E. M., Nakata, A., Chen, G., Beer, D. G., Gotoh, N., & Fujita, A. (2023). A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification. Journal of Bioinformatics and Computational Biology, 21( artigo 2350019), 1-26. doi:10.1142/S0219720023500191

    • NLM

      Relvas CEM, Nakata A, Chen G, Beer DG, Gotoh N, Fujita A. A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification [Internet]. Journal of Bioinformatics and Computational Biology. 2023 ; 21( artigo 2350019): 1-26.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S0219720023500191

    • Vancouver

      Relvas CEM, Nakata A, Chen G, Beer DG, Gotoh N, Fujita A. A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification [Internet]. Journal of Bioinformatics and Computational Biology. 2023 ; 21( artigo 2350019): 1-26.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S0219720023500191

  • Artigo de periodico

    Approaches for the identification of driver mutations in cancer: a tutorial from a computational perspective (2020)

    Cutigi, Jorge Francisco ; Evangelista, Adriane Feijó ; Simão, Adenilso da Silva

    Source: Journal of Bioinformatics and Computational Biology. Unidade: ICMC

    Subjects: NEOPLASIAS, MUTAÇÃO GENÉTICA, BIOINFORMÁTICA

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    • ABNT

      CUTIGI, Jorge Francisco e EVANGELISTA, Adriane Feijó e SIMÃO, Adenilso da Silva. Approaches for the identification of driver mutations in cancer: a tutorial from a computational perspective. Journal of Bioinformatics and Computational Biology, v. 18, n. 3, p. 2050016-1-2050016-32, 2020Tradução . . Disponível em: https://doi.org/10.1142/S021972002050016X. Acesso em: 28 abr. 2024.

    • APA

      Cutigi, J. F., Evangelista, A. F., & Simão, A. da S. (2020). Approaches for the identification of driver mutations in cancer: a tutorial from a computational perspective. Journal of Bioinformatics and Computational Biology, 18( 3), 2050016-1-2050016-32. doi:10.1142/S021972002050016X

    • NLM

      Cutigi JF, Evangelista AF, Simão A da S. Approaches for the identification of driver mutations in cancer: a tutorial from a computational perspective [Internet]. Journal of Bioinformatics and Computational Biology. 2020 ; 18( 3): 2050016-1-2050016-32.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S021972002050016X

    • Vancouver

      Cutigi JF, Evangelista AF, Simão A da S. Approaches for the identification of driver mutations in cancer: a tutorial from a computational perspective [Internet]. Journal of Bioinformatics and Computational Biology. 2020 ; 18( 3): 2050016-1-2050016-32.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S021972002050016X

  • Artigo de periodico

    Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis (2009)

    Fujita, André ; Sato, João Ricardo; Demasi, Marcos Angelo Almeida; Sogayar, Mari Cleide ; Ferreira, Carlos Eduardo ; Miyano, Satoru

    Source: Journal of Bioinformatics and Computational Biology. Unidades: IQ, IME

    Subjects: EXPRESSÃO GÊNICA, BIOQUÍMICA

    Acesso à fonteDOIHow to cite
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    • ABNT

      FUJITA, André et al. Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis. Journal of Bioinformatics and Computational Biology, v. 7, n. 4, p. 663-684, 2009Tradução . . Disponível em: https://doi.org/10.1142/S0219720009004230. Acesso em: 28 abr. 2024.

    • APA

      Fujita, A., Sato, J. R., Demasi, M. A. A., Sogayar, M. C., Ferreira, C. E., & Miyano, S. (2009). Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis. Journal of Bioinformatics and Computational Biology, 7( 4), 663-684. doi:10.1142/S0219720009004230

    • NLM

      Fujita A, Sato JR, Demasi MAA, Sogayar MC, Ferreira CE, Miyano S. Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis [Internet]. Journal of Bioinformatics and Computational Biology. 2009 ; 7( 4): 663-684.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S0219720009004230

    • Vancouver

      Fujita A, Sato JR, Demasi MAA, Sogayar MC, Ferreira CE, Miyano S. Comparing Pearson, Spearman and Hoeffding's D measure for gene expression association analysis [Internet]. Journal of Bioinformatics and Computational Biology. 2009 ; 7( 4): 663-684.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S0219720009004230

  • Artigo de periodico

    Modeling nonlinear gene regulatory networks from time series gene expression data (2008)

    Fujita, André ; Sato, João Ricardo; Garay-Malpartida, Humberto Miguel; Sogayar, Mari Cleide ; Ferreira, Carlos Eduardo ; Miyano, Satoru

    Source: Journal of Bioinformatics and Computational Biology. Unidades: EACH, IQ, IME

    Subjects: EXPRESSÃO GÊNICA, BIOQUÍMICA

    Acesso à fonteDOIHow to cite
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    • ABNT

      FUJITA, André et al. Modeling nonlinear gene regulatory networks from time series gene expression data. Journal of Bioinformatics and Computational Biology, v. 6, n. 5, p. 961-979, 2008Tradução . . Disponível em: https://doi.org/10.1142/s0219720008003746. Acesso em: 28 abr. 2024.

    • APA

      Fujita, A., Sato, J. R., Garay-Malpartida, H. M., Sogayar, M. C., Ferreira, C. E., & Miyano, S. (2008). Modeling nonlinear gene regulatory networks from time series gene expression data. Journal of Bioinformatics and Computational Biology, 6( 5), 961-979. doi:10.1142/s0219720008003746

    • NLM

      Fujita A, Sato JR, Garay-Malpartida HM, Sogayar MC, Ferreira CE, Miyano S. Modeling nonlinear gene regulatory networks from time series gene expression data [Internet]. Journal of Bioinformatics and Computational Biology. 2008 ; 6( 5): 961-979.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/s0219720008003746

    • Vancouver

      Fujita A, Sato JR, Garay-Malpartida HM, Sogayar MC, Ferreira CE, Miyano S. Modeling nonlinear gene regulatory networks from time series gene expression data [Internet]. Journal of Bioinformatics and Computational Biology. 2008 ; 6( 5): 961-979.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/s0219720008003746

  • Artigo de periodico

    Modeling cancer: integration of "omics" information in dynamic systems (2007)

    Stransky, Beatriz; Barrera, Júnior; Ohno-Machado, Lucila; Souza, Sandro J. de

    Source: Journal of Bioinformatics and Computational Biology. Unidade: IME

    Subjects: SISTEMAS DINÂMICOS, CÂNCER, BIOINFORMÁTICA

    Acesso à fonteDOIHow to cite
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    • ABNT

      STRANSKY, Beatriz et al. Modeling cancer: integration of "omics" information in dynamic systems. Journal of Bioinformatics and Computational Biology, 2007Tradução . . Disponível em: https://doi.org/10.1142/S0219720007002990. Acesso em: 28 abr. 2024.

    • APA

      Stransky, B., Barrera, J., Ohno-Machado, L., & Souza, S. J. de. (2007). Modeling cancer: integration of "omics" information in dynamic systems. Journal of Bioinformatics and Computational Biology. doi:10.1142/S0219720007002990

    • NLM

      Stransky B, Barrera J, Ohno-Machado L, Souza SJ de. Modeling cancer: integration of "omics" information in dynamic systems [Internet]. Journal of Bioinformatics and Computational Biology. 2007 ;[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S0219720007002990

    • Vancouver

      Stransky B, Barrera J, Ohno-Machado L, Souza SJ de. Modeling cancer: integration of "omics" information in dynamic systems [Internet]. Journal of Bioinformatics and Computational Biology. 2007 ;[citado 2024 abr. 28 ] Available from: https://doi.org/10.1142/S0219720007002990
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