ReP USP - Resultado da busca

Artigo de periodico
Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs (2015)
Nakata, Asuka; Yoshida, Ryo ; Yamaguchi, Rui ; Yamauchi, Mai; Tamada, Yoshinori ; Fujita, André ; Shimamura, Teppei ; Imoto, Seiya ; Higuchi, Tomoyuki ; Nomura, Masaharu; Kimura, Tatsuo ; Nokihara, Hiroshi ; Higashiyama, Masahiko; Kondoh, Kazuya; Nishihara, Hiroshi ; Tojo, Arinobu ; Yano, Seiji ; Miyano, Satoru ; Gotoh, Noriko
Source: Scientific Reports. Unidade: IME
Subjects: BIOINFORMÁTICA, NEOPLASIAS PULMONARES
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ABNT
NAKATA, Asuka et al. Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs. Scientific Reports, v. 5, 2015Tradução . . Disponível em: https://doi.org/10.1038/srep13076. Acesso em: 02 out. 2024.
APA
Nakata, A., Yoshida, R., Yamaguchi, R., Yamauchi, M., Tamada, Y., Fujita, A., et al. (2015). Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs. Scientific Reports, 5. doi:10.1038/srep13076
NLM
Nakata A, Yoshida R, Yamaguchi R, Yamauchi M, Tamada Y, Fujita A, Shimamura T, Imoto S, Higuchi T, Nomura M, Kimura T, Nokihara H, Higashiyama M, Kondoh K, Nishihara H, Tojo A, Yano S, Miyano S, Gotoh N. Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs [Internet]. Scientific Reports. 2015 ; 5[citado 2024 out. 02 ] Available from: https://doi.org/10.1038/srep13076
Vancouver
Nakata A, Yoshida R, Yamaguchi R, Yamauchi M, Tamada Y, Fujita A, Shimamura T, Imoto S, Higuchi T, Nomura M, Kimura T, Nokihara H, Higashiyama M, Kondoh K, Nishihara H, Tojo A, Yano S, Miyano S, Gotoh N. Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs [Internet]. Scientific Reports. 2015 ; 5[citado 2024 out. 02 ] Available from: https://doi.org/10.1038/srep13076
Parte de monografia/livro
A tutorial to identify nonlinear associations in gene expression time series data (2014)
Fujita, André ; Miyano, Satoru
Source: Transcription factor regulatory networks: methods and protocols. Unidade: IME
Subjects: BIOINFORMÁTICA, ANÁLISE DE SÉRIES TEMPORAIS, ANÁLISE MULTIVARIADA
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ABNT
FUJITA, André e MIYANO, Satoru. A tutorial to identify nonlinear associations in gene expression time series data. Transcription factor regulatory networks: methods and protocols. Tradução . New York: Humana Press, 2014. . Disponível em: https://doi.org/10.1007/978-1-4939-0805-9_8. Acesso em: 02 out. 2024.
APA
Fujita, A., & Miyano, S. (2014). A tutorial to identify nonlinear associations in gene expression time series data. In Transcription factor regulatory networks: methods and protocols. New York: Humana Press. doi:10.1007/978-1-4939-0805-9_8
NLM
Fujita A, Miyano S. A tutorial to identify nonlinear associations in gene expression time series data [Internet]. In: Transcription factor regulatory networks: methods and protocols. New York: Humana Press; 2014. [citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-1-4939-0805-9_8
Vancouver
Fujita A, Miyano S. A tutorial to identify nonlinear associations in gene expression time series data [Internet]. In: Transcription factor regulatory networks: methods and protocols. New York: Humana Press; 2014. [citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-1-4939-0805-9_8
Artigo de periodico
XiP: a computational environment to create, extend and share workflows (2013)
Nagasaki, Masao ; Fujita, André ; Sekiya, Yayoi; Saito, Ayumu ; Ikeda, Emi; Li, Chen; Miyano, Satoru
Source: Bioinformatics. Unidade: IME
Assunto: PROGRAMAÇÃO INTEIRA E FLUXOS EM REDE
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ABNT
NAGASAKI, Masao et al. XiP: a computational environment to create, extend and share workflows. Bioinformatics, v. 29, n. 1, p. 137-139, 2013Tradução . . Disponível em: https://doi.org/10.1093/bioinformatics/bts630. Acesso em: 02 out. 2024.
APA
Nagasaki, M., Fujita, A., Sekiya, Y., Saito, A., Ikeda, E., Li, C., & Miyano, S. (2013). XiP: a computational environment to create, extend and share workflows. Bioinformatics, 29( 1), 137-139. doi:10.1093/bioinformatics/bts630
NLM
Nagasaki M, Fujita A, Sekiya Y, Saito A, Ikeda E, Li C, Miyano S. XiP: a computational environment to create, extend and share workflows [Internet]. Bioinformatics. 2013 ; 29( 1): 137-139.[citado 2024 out. 02 ] Available from: https://doi.org/10.1093/bioinformatics/bts630
Vancouver
Nagasaki M, Fujita A, Sekiya Y, Saito A, Ikeda E, Li C, Miyano S. XiP: a computational environment to create, extend and share workflows [Internet]. Bioinformatics. 2013 ; 29( 1): 137-139.[citado 2024 out. 02 ] Available from: https://doi.org/10.1093/bioinformatics/bts630
Artigo de periodico
Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing (2012)
Kojima, Kaname ; Imoto, Seiya ; Yamaguchi, Rui ; Fujita, André ; Yamaouchi, Mai; Gotoh, Noriko ; Miyano, Satoru
Source: BMC Genomics. Unidade: IME
Assunto: GENOMAS
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ABNT
KOJIMA, Kaname et al. Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing. BMC Genomics, v. 13, p. 1-14, 2012Tradução . . Disponível em: https://doi.org/10.1186/1471-2164-13-S1-S6. Acesso em: 02 out. 2024.
APA
Kojima, K., Imoto, S., Yamaguchi, R., Fujita, A., Yamaouchi, M., Gotoh, N., & Miyano, S. (2012). Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing. BMC Genomics, 13, 1-14. doi:10.1186/1471-2164-13-S1-S6
NLM
Kojima K, Imoto S, Yamaguchi R, Fujita A, Yamaouchi M, Gotoh N, Miyano S. Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing [Internet]. BMC Genomics. 2012 ; 13 1-14.[citado 2024 out. 02 ] Available from: https://doi.org/10.1186/1471-2164-13-S1-S6
Vancouver
Kojima K, Imoto S, Yamaguchi R, Fujita A, Yamaouchi M, Gotoh N, Miyano S. Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing [Internet]. BMC Genomics. 2012 ; 13 1-14.[citado 2024 out. 02 ] Available from: https://doi.org/10.1186/1471-2164-13-S1-S6
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 out. 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 out. 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 out. 02 ] Available from: https://doi.org/10.1186/1752-0509-6-137
Artigo de periodico
Systems biology model repository for macrophage pathway simulation (2011)
Nagasawa, Masao; Saito, Ayumu ; Fujita, André ; Tremmel, Georg ; Ueno, Kazuko ; Ikeda, Emi; Jeong, Euna ; Miyano, Satoru
Source: Bioinformatics. Unidade: IME
Assunto: BIOINFORMÁTICA
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ABNT
NAGASAWA, Masao et al. Systems biology model repository for macrophage pathway simulation. Bioinformatics, v. 27, n. 11, p. 1591-1593, 2011Tradução . . Disponível em: https://doi.org/10.1093/bioinformatics/btr173. Acesso em: 02 out. 2024.
APA
Nagasawa, M., Saito, A., Fujita, A., Tremmel, G., Ueno, K., Ikeda, E., et al. (2011). Systems biology model repository for macrophage pathway simulation. Bioinformatics, 27( 11), 1591-1593. doi:10.1093/bioinformatics/btr173
NLM
Nagasawa M, Saito A, Fujita A, Tremmel G, Ueno K, Ikeda E, Jeong E, Miyano S. Systems biology model repository for macrophage pathway simulation [Internet]. Bioinformatics. 2011 ; 27( 11): 1591-1593.[citado 2024 out. 02 ] Available from: https://doi.org/10.1093/bioinformatics/btr173
Vancouver
Nagasawa M, Saito A, Fujita A, Tremmel G, Ueno K, Ikeda E, Jeong E, Miyano S. Systems biology model repository for macrophage pathway simulation [Internet]. Bioinformatics. 2011 ; 27( 11): 1591-1593.[citado 2024 out. 02 ] Available from: https://doi.org/10.1093/bioinformatics/btr173
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
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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 out. 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 out. 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 out. 02 ] Available from: https://doi.org/10.1109/tcbb.2010.40
Monografia/livro-ed/org
Advances in bioinformatics and computational biology (2010)
Ferreira, Carlos Eduardo (Editor) ; Miyano, Satoru (Editor); Stadler, Peter F. (Editor)
Conference titles: Brazilian Symposium on Bioinformatics- BSB. Unidade: IME
Subjects: INTELIGÊNCIA ARTIFICIAL, BIOINFORMÁTICA
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ABNT
Advances in bioinformatics and computational biology. . Berlin: Springer. Disponível em: https://doi.org/10.1007/978-3-642-15060-9. Acesso em: 02 out. 2024. , 2010
APA
Advances in bioinformatics and computational biology. (2010). Advances in bioinformatics and computational biology. Berlin: Springer. doi:10.1007/978-3-642-15060-9
NLM
Advances in bioinformatics and computational biology [Internet]. 2010 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-3-642-15060-9
Vancouver
Advances in bioinformatics and computational biology [Internet]. 2010 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1007/978-3-642-15060-9
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 out. 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 out. 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 out. 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 out. 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 out. 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 out. 02 ] Available from: https://doi.org/10.1142/s0219720008003746

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