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Artigo de periodico
Analysis of clonal evolution in cancer: a computational perspective (2025)
Ribeiro, Paulo Henrique ; Simão, Adenilso da Silva
Source: Journal of Bioinformatics and Computational Biology. Unidade: ICMC
Subjects: NEOPLASIAS, BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIBEIRO, Paulo Henrique e SIMÃO, Adenilso da Silva. Analysis of clonal evolution in cancer: a computational perspective. Journal of Bioinformatics and Computational Biology, v. 23, n. 2, p. 2531001-1-2531001-32, 2025Tradução . . Disponível em: https://doi.org/10.1142/S0219720025310018. Acesso em: 16 jun. 2025.
APA
Ribeiro, P. H., & Simão, A. da S. (2025). Analysis of clonal evolution in cancer: a computational perspective. Journal of Bioinformatics and Computational Biology, 23( 2), 2531001-1-2531001-32. doi:10.1142/S0219720025310018
NLM
Ribeiro PH, Simão A da S. Analysis of clonal evolution in cancer: a computational perspective [Internet]. Journal of Bioinformatics and Computational Biology. 2025 ; 23( 2): 2531001-1-2531001-32.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1142/S0219720025310018
Vancouver
Ribeiro PH, Simão A da S. Analysis of clonal evolution in cancer: a computational perspective [Internet]. Journal of Bioinformatics and Computational Biology. 2025 ; 23( 2): 2531001-1-2531001-32.[citado 2025 jun. 16 ] Available from: https://doi.org/10.1142/S0219720025310018
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 16 jun. 2025.
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 2025 jun. 16 ] 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 2025 jun. 16 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 16 jun. 2025.
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 2025 jun. 16 ] 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 2025 jun. 16 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 16 jun. 2025.
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 2025 jun. 16 ] 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 2025 jun. 16 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 16 jun. 2025.
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 2025 jun. 16 ] 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 2025 jun. 16 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 16 jun. 2025.
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 2025 jun. 16 ] 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 2025 jun. 16 ] Available from: https://doi.org/10.1142/S0219720007002990

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