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Trabalho de evento-resumo periodico
Intracellular calcium and neural transcription factor expression oscillations coding the fate of neurogenesis (2016)
Glaser, Talita; Kageyama, R; Ulrich, Henning
Source: Cell Transplantation. Conference titles: Annual Meeting of the American Society for Neural Therapy and Repair. Unidade: IQ
Subjects: FATORES DE TRANSCRIÇÃO, BIOQUÍMICA, SISTEMA NERVOSO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GLASER, Talita e KAGEYAMA, R e ULRICH, Henning. Intracellular calcium and neural transcription factor expression oscillations coding the fate of neurogenesis. Cell Transplantation. New York: Instituto de Química, Universidade de São Paulo. . Acesso em: 03 nov. 2024. , 2016
APA
Glaser, T., Kageyama, R., & Ulrich, H. (2016). Intracellular calcium and neural transcription factor expression oscillations coding the fate of neurogenesis. Cell Transplantation. New York: Instituto de Química, Universidade de São Paulo.
NLM
Glaser T, Kageyama R, Ulrich H. Intracellular calcium and neural transcription factor expression oscillations coding the fate of neurogenesis. Cell Transplantation. 2016 ; 25 758.[citado 2024 nov. 03 ]
Vancouver
Glaser T, Kageyama R, Ulrich H. Intracellular calcium and neural transcription factor expression oscillations coding the fate of neurogenesis. Cell Transplantation. 2016 ; 25 758.[citado 2024 nov. 03 ]
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: 03 nov. 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 nov. 03 ] 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 nov. 03 ] 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: 03 nov. 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 nov. 03 ] 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 nov. 03 ] Available from: https://doi.org/10.1109/tcbb.2010.40
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: 03 nov. 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 nov. 03 ] 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 nov. 03 ] 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: 03 nov. 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 nov. 03 ] 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 nov. 03 ] Available from: https://doi.org/10.1142/s0219720008003746

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