ReP USP - Resultado da busca

Parte de monografia/livro
ANOCVA: a nonparametric statistical test to compare clustering structures (2018)
Patriota, Alexandre Galvão ; Vidal, Maciel Calebe; Jesus, Davi Augusto Caetano de; Fujita, André
Fonte: Theoretical and applied aspects of systems biology. Unidade: IME
Assuntos: BIOINFORMÁTICA, BIOESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PATRIOTA, Alexandre Galvão et al. ANOCVA: a nonparametric statistical test to compare clustering structures. Theoretical and applied aspects of systems biology. Tradução . Cham: Springer, 2018. . Disponível em: https://doi.org/10.1007/978-3-319-74974-7_6. Acesso em: 15 nov. 2025.
APA
Patriota, A. G., Vidal, M. C., Jesus, D. A. C. de, & Fujita, A. (2018). ANOCVA: a nonparametric statistical test to compare clustering structures. In Theoretical and applied aspects of systems biology. Cham: Springer. doi:10.1007/978-3-319-74974-7_6
NLM
Patriota AG, Vidal MC, Jesus DAC de, Fujita A. ANOCVA: a nonparametric statistical test to compare clustering structures [Internet]. In: Theoretical and applied aspects of systems biology. Cham: Springer; 2018. [citado 2025 nov. 15 ] Available from: https://doi.org/10.1007/978-3-319-74974-7_6
Vancouver
Patriota AG, Vidal MC, Jesus DAC de, Fujita A. ANOCVA: a nonparametric statistical test to compare clustering structures [Internet]. In: Theoretical and applied aspects of systems biology. Cham: Springer; 2018. [citado 2025 nov. 15 ] Available from: https://doi.org/10.1007/978-3-319-74974-7_6
Artigo de periodico
Identification of alterations associated with age in the clustering structure of functional brain networks (2018)
Guzman, Grover Enrique Castro ; Sato, João Ricardo ; Vidal, Maciel Calebe ; Fujita, André
Fonte: PLOS ONE. Unidade: IME
Assunto: BIOINFORMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUZMAN, Grover Enrique Castro et al. Identification of alterations associated with age in the clustering structure of functional brain networks. PLOS ONE, v. 13, n. 5 , p. 1-14, 2018Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0195906. Acesso em: 15 nov. 2025.
APA
Guzman, G. E. C., Sato, J. R., Vidal, M. C., & Fujita, A. (2018). Identification of alterations associated with age in the clustering structure of functional brain networks. PLOS ONE, 13( 5 ), 1-14. doi:10.1371/journal.pone.0195906
NLM
Guzman GEC, Sato JR, Vidal MC, Fujita A. Identification of alterations associated with age in the clustering structure of functional brain networks [Internet]. PLOS ONE. 2018 ; 13( 5 ): 1-14.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1371/journal.pone.0195906
Vancouver
Guzman GEC, Sato JR, Vidal MC, Fujita A. Identification of alterations associated with age in the clustering structure of functional brain networks [Internet]. PLOS ONE. 2018 ; 13( 5 ): 1-14.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1371/journal.pone.0195906
Artigo de periodico
Complex network measures in autism spectrum disorders (2018)
Sato, João Ricardo ; Vidal, Maciel Calebe ; Santos, Suzana de Siqueira ; Massirer, Katlin Brauer ; Fujita, André
Fonte: IEEE - ACM Transactions on Computational Biology and Bioinformatics. Unidade: IME
Assuntos: BIOINFORMÁTICA, REDES COMPLEXAS, AUTISMO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SATO, João Ricardo et al. Complex network measures in autism spectrum disorders. IEEE - ACM Transactions on Computational Biology and Bioinformatics, v. 15, n. 2, p. 581 - 587, 2018Tradução . . Disponível em: https://doi.org/10.1109/TCBB.2015.2476787. Acesso em: 15 nov. 2025.
APA
Sato, J. R., Vidal, M. C., Santos, S. de S., Massirer, K. B., & Fujita, A. (2018). Complex network measures in autism spectrum disorders. IEEE - ACM Transactions on Computational Biology and Bioinformatics, 15( 2), 581 - 587. doi:10.1109/TCBB.2015.2476787
NLM
Sato JR, Vidal MC, Santos S de S, Massirer KB, Fujita A. Complex network measures in autism spectrum disorders [Internet]. IEEE - ACM Transactions on Computational Biology and Bioinformatics. 2018 ; 15( 2): 581 - 587.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1109/TCBB.2015.2476787
Vancouver
Sato JR, Vidal MC, Santos S de S, Massirer KB, Fujita A. Complex network measures in autism spectrum disorders [Internet]. IEEE - ACM Transactions on Computational Biology and Bioinformatics. 2018 ; 15( 2): 581 - 587.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1109/TCBB.2015.2476787
Artigo de periodico
Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis (2016)
Sato, João Ricardo ; Balardin, Joana Bisol ; Vidal, Maciel Calebe ; Fujita, André
Fonte: Journal of Psychiatry and Neuroscience. Unidade: IME
Assuntos: BIOINFORMÁTICA, ESTATÍSTICA COMPUTACIONAL, AUTISMO, CRIANÇAS AUTISTAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SATO, João Ricardo et al. Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis. Journal of Psychiatry and Neuroscience, v. 41, n. 2, p. 124-132, 2016Tradução . . Disponível em: https://doi.org/10.1503/jpn.140364. Acesso em: 15 nov. 2025.
APA
Sato, J. R., Balardin, J. B., Vidal, M. C., & Fujita, A. (2016). Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis. Journal of Psychiatry and Neuroscience, 41( 2), 124-132. doi:10.1503/jpn.140364
NLM
Sato JR, Balardin JB, Vidal MC, Fujita A. Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis [Internet]. Journal of Psychiatry and Neuroscience. 2016 ; 41( 2): 124-132.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1503/jpn.140364
Vancouver
Sato JR, Balardin JB, Vidal MC, Fujita A. Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis [Internet]. Journal of Psychiatry and Neuroscience. 2016 ; 41( 2): 124-132.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1503/jpn.140364
Artigo de periodico
Complex network measures in autism spectrum disorders (2015)
Sato, João Ricardo; Vidal, Maciel Calebe; Santos, Suzana de Siqueira; Massirer, Katlin Brauer; Fujita, André
Fonte: IEEE/ACM Transactions on Computational Biology and Bioinformatics. Unidade: IME
Assuntos: BIOINFORMÁTICA, NEUROCIÊNCIAS, AUTISMO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SATO, João Ricardo et al. Complex network measures in autism spectrum disorders. IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. 15, n. 2, p. 581-587, 2015Tradução . . Disponível em: https://doi.org/10.1109/TCBB.2015.2476787. Acesso em: 15 nov. 2025.
APA
Sato, J. R., Vidal, M. C., Santos, S. de S., Massirer, K. B., & Fujita, A. (2015). Complex network measures in autism spectrum disorders. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15( 2), 581-587. doi:10.1109/TCBB.2015.2476787
NLM
Sato JR, Vidal MC, Santos S de S, Massirer KB, Fujita A. Complex network measures in autism spectrum disorders [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2015 ; 15( 2): 581-587.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1109/TCBB.2015.2476787
Vancouver
Sato JR, Vidal MC, Santos S de S, Massirer KB, Fujita A. Complex network measures in autism spectrum disorders [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2015 ; 15( 2): 581-587.[citado 2025 nov. 15 ] Available from: https://doi.org/10.1109/TCBB.2015.2476787

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