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Artigo de periodico
Functional clustering of time series gene expression data by Granger causality (2012)
Fujita, André ; Severino, Patrícia ; Kaname, Kojima ; Sato, João Ricardo ; Patriota, Alexandre Galvão ; Miyano, Satoru
Source: BMC Systems Biology. Unidade: IME
Subjects: BIOQUÍMICA, ANÁLISE DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FUJITA, André et al. Functional clustering of time series gene expression data by Granger causality. BMC Systems Biology, v. 6, n. 137, p. 1-12, 2012Tradução . . Disponível em: https://doi.org/10.1186/1752-0509-6-137. Acesso em: 02 jun. 2024.
APA
Fujita, A., Severino, P., Kaname, K., Sato, J. R., Patriota, A. G., & Miyano, S. (2012). Functional clustering of time series gene expression data by Granger causality. BMC Systems Biology, 6( 137), 1-12. doi:10.1186/1752-0509-6-137
NLM
Fujita A, Severino P, Kaname K, Sato JR, Patriota AG, Miyano S. Functional clustering of time series gene expression data by Granger causality [Internet]. BMC Systems Biology. 2012 ; 6( 137): 1-12.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1186/1752-0509-6-137
Vancouver
Fujita A, Severino P, Kaname K, Sato JR, Patriota AG, Miyano S. Functional clustering of time series gene expression data by Granger causality [Internet]. BMC Systems Biology. 2012 ; 6( 137): 1-12.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1186/1752-0509-6-137
Artigo de periodico
Inferring contagion in regulatory networks (2011)
Fujita, André ; Sato, João Ricardo ; Demasi, Marcos Angelo Almeida ; Yamaguchi, Rui ; Shimamura, Teppei ; Ferreira, Carlos Eduardo ; Sogayar, Mari Cleide ; Miyano, Satoru
Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics. Unidades: IME, IQ
Subjects: REGULAÇÃO GÊNICA, BIOQUÍMICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FUJITA, André et al. Inferring contagion in regulatory networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. 8, n. 2, p. 570-576, 2011Tradução . . Disponível em: https://doi.org/10.1109/tcbb.2010.40. Acesso em: 02 jun. 2024.
APA
Fujita, A., Sato, J. R., Demasi, M. A. A., Yamaguchi, R., Shimamura, T., Ferreira, C. E., et al. (2011). Inferring contagion in regulatory networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8( 2), 570-576. doi:10.1109/tcbb.2010.40
NLM
Fujita A, Sato JR, Demasi MAA, Yamaguchi R, Shimamura T, Ferreira CE, Sogayar MC, Miyano S. Inferring contagion in regulatory networks [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2011 ; 8( 2): 570-576.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1109/tcbb.2010.40
Vancouver
Fujita A, Sato JR, Demasi MAA, Yamaguchi R, Shimamura T, Ferreira CE, Sogayar MC, Miyano S. Inferring contagion in regulatory networks [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2011 ; 8( 2): 570-576.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1109/tcbb.2010.40
Artigo de periodico
Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis (2010)
Sato, João Ricardo ; Fujita, André ; Cardoso, Elisson F.; Thomaz, Carlos E.; Brammer, Michael J.; Amaro Jr., Edson
Source: NeuroImage. Unidade: FM
Subjects: CAUSALIDADE, CÉREBRO (FISIOLOGIA), IMAGEM POR RESSONÂNCIA MAGNÉTICA, PROCESSOS COGNITIVOS, ANÁLISE DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SATO, João Ricardo et al. Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis. NeuroImage, v. 52, n. 4, p. 1444-1455, 2010Tradução . . Disponível em: https://doi.org/10.1016/j.neuroimage.2010.06.018. Acesso em: 02 jun. 2024.
APA
Sato, J. R., Fujita, A., Cardoso, E. F., Thomaz, C. E., Brammer, M. J., & Amaro Jr., E. (2010). Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis. NeuroImage, 52( 4), 1444-1455. doi:10.1016/j.neuroimage.2010.06.018
NLM
Sato JR, Fujita A, Cardoso EF, Thomaz CE, Brammer MJ, Amaro Jr. E. Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis [Internet]. NeuroImage. 2010 ; 52( 4): 1444-1455.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.neuroimage.2010.06.018
Vancouver
Sato JR, Fujita A, Cardoso EF, Thomaz CE, Brammer MJ, Amaro Jr. E. Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis [Internet]. NeuroImage. 2010 ; 52( 4): 1444-1455.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.neuroimage.2010.06.018
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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] 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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] Available from: https://doi.org/10.1142/s0219720008003746

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