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Dissertação (Mestrado)
Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground (2022)
Biazzi, Renata Biaggi ; Fujita, André (Orientador) ; Takahashi, Daniel Yasumasa (coorient)
Unidade: BIOINFORMÁTICA
Subjects: ALGORITMOS, MORFOLOGIA (ANATOMIA), SELEÇÃO NATURAL
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ABNT
BIAZZI, Renata Biaggi. Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground. 2022. Dissertação (Mestrado) – Universidade de São Paulo, São Paulo, 2022. Disponível em: https://www.teses.usp.br/teses/disponiveis/95/95131/tde-19092022-143101/. Acesso em: 04 jun. 2024.
APA
Biazzi, R. B. (2022). Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground (Dissertação (Mestrado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/95/95131/tde-19092022-143101/
NLM
Biazzi RB. Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground [Internet]. 2022 ;[citado 2024 jun. 04 ] Available from: https://www.teses.usp.br/teses/disponiveis/95/95131/tde-19092022-143101/
Vancouver
Biazzi RB. Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground [Internet]. 2022 ;[citado 2024 jun. 04 ] Available from: https://www.teses.usp.br/teses/disponiveis/95/95131/tde-19092022-143101/
Artigo de periodico
A fast parameter estimator for large complex networks (2022)
Guzman, Grover Enrique Castro ; Takahashi, Daniel Yasumasa; Fujita, André
Source: Journal of Complex Networks. Unidade: IME
Subjects: COMBINATÓRIA, TEORIA DOS GRAFOS
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ABNT
GUZMAN, Grover Enrique Castro e TAKAHASHI, Daniel Yasumasa e FUJITA, André. A fast parameter estimator for large complex networks. Journal of Complex Networks, v. 10, n. artigo cnac022. p. 1-11, 2022Tradução . . Disponível em: https://doi.org/10.1093/comnet/cnac022. Acesso em: 04 jun. 2024.
APA
Guzman, G. E. C., Takahashi, D. Y., & Fujita, A. (2022). A fast parameter estimator for large complex networks. Journal of Complex Networks, 10( artigo cnac022. p. 1-11). doi:10.1093/comnet/cnac022
NLM
Guzman GEC, Takahashi DY, Fujita A. A fast parameter estimator for large complex networks [Internet]. Journal of Complex Networks. 2022 ; 10( artigo cnac022. p. 1-11):[citado 2024 jun. 04 ] Available from: https://doi.org/10.1093/comnet/cnac022
Vancouver
Guzman GEC, Takahashi DY, Fujita A. A fast parameter estimator for large complex networks [Internet]. Journal of Complex Networks. 2022 ; 10( artigo cnac022. p. 1-11):[citado 2024 jun. 04 ] Available from: https://doi.org/10.1093/comnet/cnac022
Artigo de periodico
Heart rate variability predicts the subject-driven cognitive states (2022)
Farfán, Carlos Enrique Paucar ; Bruel, Pedro ; Goldman, Alfredo ; Takahashi, Daniel Yasumasa ; Fujita, André
Source: Research Square. Unidade: IME
Assunto: BIOINFORMÁTICA
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ABNT
FARFÁN, Carlos Enrique Paucar et al. Heart rate variability predicts the subject-driven cognitive states. Research Square, 2022Tradução . . Disponível em: https://doi.org/10.21203/rs.3.rs-1957712/v1. Acesso em: 04 jun. 2024.
APA
Farfán, C. E. P., Bruel, P., Goldman, A., Takahashi, D. Y., & Fujita, A. (2022). Heart rate variability predicts the subject-driven cognitive states. Research Square. doi:10.21203/rs.3.rs-1957712/v1
NLM
Farfán CEP, Bruel P, Goldman A, Takahashi DY, Fujita A. Heart rate variability predicts the subject-driven cognitive states [Internet]. Research Square. 2022 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.21203/rs.3.rs-1957712/v1
Vancouver
Farfán CEP, Bruel P, Goldman A, Takahashi DY, Fujita A. Heart rate variability predicts the subject-driven cognitive states [Internet]. Research Square. 2022 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.21203/rs.3.rs-1957712/v1
Trabalho de evento
Predicting soft robot's locomotion fitness (2021)
Biazzi, Renata Biaggi ; Fujita, André ; Takahashi, Daniel Yasumasa
Source: Proceedings. Conference titles: Genetic and Evolutionary Computation Conference Companion - GECCO. Unidades: IME, BIOINFORMÁTICA
Subjects: ROBÓTICA, LOCOMOÇÃO
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ABNT
BIAZZI, Renata Biaggi e FUJITA, André e TAKAHASHI, Daniel Yasumasa. Predicting soft robot's locomotion fitness. 2021, Anais.. New York: ACM, 2021. Disponível em: https://doi.org/10.1145/3449726.3459417. Acesso em: 04 jun. 2024.
APA
Biazzi, R. B., Fujita, A., & Takahashi, D. Y. (2021). Predicting soft robot's locomotion fitness. In Proceedings. New York: ACM. doi:10.1145/3449726.3459417
NLM
Biazzi RB, Fujita A, Takahashi DY. Predicting soft robot's locomotion fitness [Internet]. Proceedings. 2021 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.1145/3449726.3459417
Vancouver
Biazzi RB, Fujita A, Takahashi DY. Predicting soft robot's locomotion fitness [Internet]. Proceedings. 2021 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.1145/3449726.3459417
Artigo de periodico
A semi-parametric statistical test to compare complex networks (2020)
Fujita, André ; Lira, Eduardo Silva ; Santos, Suzana de Siqueira ; Bando, Sílvia Yumi ; Soares, Gabriela Eleuterio ; Takahashi, Daniel Yasumasa
Source: Journal of Complex Networks. Unidades: IME, FM, EEFERP
Subjects: INFERÊNCIA PARAMÉTRICA, BIOINFORMÁTICA
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ABNT
FUJITA, André et al. A semi-parametric statistical test to compare complex networks. Journal of Complex Networks, v. 8, n. 2, 2020Tradução . . Disponível em: https://doi.org/10.1093/comnet/cnz028. Acesso em: 04 jun. 2024.
APA
Fujita, A., Lira, E. S., Santos, S. de S., Bando, S. Y., Soares, G. E., & Takahashi, D. Y. (2020). A semi-parametric statistical test to compare complex networks. Journal of Complex Networks, 8( 2). doi:10.1093/comnet/cnz028
NLM
Fujita A, Lira ES, Santos S de S, Bando SY, Soares GE, Takahashi DY. A semi-parametric statistical test to compare complex networks [Internet]. Journal of Complex Networks. 2020 ; 8( 2):[citado 2024 jun. 04 ] Available from: https://doi.org/10.1093/comnet/cnz028
Vancouver
Fujita A, Lira ES, Santos S de S, Bando SY, Soares GE, Takahashi DY. A semi-parametric statistical test to compare complex networks [Internet]. Journal of Complex Networks. 2020 ; 8( 2):[citado 2024 jun. 04 ] Available from: https://doi.org/10.1093/comnet/cnz028
Artigo de periodico
Correlation between graphs with an application to brain network analysis (2017)
Fujita, André ; Takahashi, Daniel Yasumasa ; Balardin, Joana Bisol ; Vidal, Maciel Calebe ; Sato, João Ricardo
Source: Computational Statistics and Data Analysis. Unidade: IME
Assunto: REDES NEURAIS
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ABNT
FUJITA, André et al. Correlation between graphs with an application to brain network analysis. Computational Statistics and Data Analysis, v. 109, p. 76-92, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.csda.2016.11.016. Acesso em: 04 jun. 2024.
APA
Fujita, A., Takahashi, D. Y., Balardin, J. B., Vidal, M. C., & Sato, J. R. (2017). Correlation between graphs with an application to brain network analysis. Computational Statistics and Data Analysis, 109, 76-92. doi:10.1016/j.csda.2016.11.016
NLM
Fujita A, Takahashi DY, Balardin JB, Vidal MC, Sato JR. Correlation between graphs with an application to brain network analysis [Internet]. Computational Statistics and Data Analysis. 2017 ; 109 76-92.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1016/j.csda.2016.11.016
Vancouver
Fujita A, Takahashi DY, Balardin JB, Vidal MC, Sato JR. Correlation between graphs with an application to brain network analysis [Internet]. Computational Statistics and Data Analysis. 2017 ; 109 76-92.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1016/j.csda.2016.11.016
Artigo de periodico
A statistical method to distinguish functional brain networks (2017)
Fujita, André ; Vidal, Maciel Calebe ; Takahashi, Daniel Yasumasa
Source: Frontiers in Neuroscience. Unidade: IME
Subjects: ANÁLISE DE VARIÂNCIA, GRAFOS ALEATÓRIOS, SIMULAÇÃO, ESTATÍSTICA APLICADA, CIÊNCIA DA COMPUTAÇÃO
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ABNT
FUJITA, André e VIDAL, Maciel Calebe e TAKAHASHI, Daniel Yasumasa. A statistical method to distinguish functional brain networks. Frontiers in Neuroscience, v. 11, p. 1-10, 2017Tradução . . Disponível em: https://doi.org/10.3389/fnins.2017.00066. Acesso em: 04 jun. 2024.
APA
Fujita, A., Vidal, M. C., & Takahashi, D. Y. (2017). A statistical method to distinguish functional brain networks. Frontiers in Neuroscience, 11, 1-10. doi:10.3389/fnins.2017.00066
NLM
Fujita A, Vidal MC, Takahashi DY. A statistical method to distinguish functional brain networks [Internet]. Frontiers in Neuroscience. 2017 ; 11 1-10.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fnins.2017.00066
Vancouver
Fujita A, Vidal MC, Takahashi DY. A statistical method to distinguish functional brain networks [Internet]. Frontiers in Neuroscience. 2017 ; 11 1-10.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fnins.2017.00066
Artigo de periodico
ANOCVA in R: a software to compare clusters between groups and its application to the study of autism spectrum disorder (2017)
Vidal, Maciel Calebe ; Sato, João Ricardo ; Balardin, Joana Bisol ; Takahashi, Daniel Yasumasa ; Fujita, André
Source: Frontiers in Neuroscience. Unidade: IME
Subjects: CIÊNCIA DA COMPUTAÇÃO, CIÊNCIA DA COMPUTAÇÃO, ESTATÍSTICA, ANÁLISE DE VARIÂNCIA
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ABNT
VIDAL, Maciel Calebe et al. ANOCVA in R: a software to compare clusters between groups and its application to the study of autism spectrum disorder. Frontiers in Neuroscience, v. 11, p. 1-8, 2017Tradução . . Disponível em: https://doi.org/10.3389/fnins.2017.00016. Acesso em: 04 jun. 2024.
APA
Vidal, M. C., Sato, J. R., Balardin, J. B., Takahashi, D. Y., & Fujita, A. (2017). ANOCVA in R: a software to compare clusters between groups and its application to the study of autism spectrum disorder. Frontiers in Neuroscience, 11, 1-8. doi:10.3389/fnins.2017.00016
NLM
Vidal MC, Sato JR, Balardin JB, Takahashi DY, Fujita A. ANOCVA in R: a software to compare clusters between groups and its application to the study of autism spectrum disorder [Internet]. Frontiers in Neuroscience. 2017 ;11 1-8.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fnins.2017.00016
Vancouver
Vidal MC, Sato JR, Balardin JB, Takahashi DY, Fujita A. ANOCVA in R: a software to compare clusters between groups and its application to the study of autism spectrum disorder [Internet]. Frontiers in Neuroscience. 2017 ;11 1-8.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fnins.2017.00016
Parte de monografia/livro
Statistical methods in graphs: parameter estimation, model selection, and hypothesis test (2016)
Santos, Suzana de Siqueira; Takahashi, Daniel Yasumasa; Sato, João Ricardo; Ferreira, Carlos Eduardo ; Fujita, André
Source: Mathematical foundations and applications of graph entropy. Unidade: IME
Subjects: TEORIA DOS GRAFOS, PROBABILIDADE, ESTIMAÇÃO PARAMÉTRICA, TESTES DE HIPÓTESES, SELEÇÃO DE MODELOS, BIOESTATÍSTICA
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ABNT
SANTOS, Suzana de Siqueira et al. Statistical methods in graphs: parameter estimation, model selection, and hypothesis test. Mathematical foundations and applications of graph entropy. Tradução . Weinheim: Wiley-VCH, 2016. . Disponível em: https://doi.org/10.1002/9783527693245.ch6. Acesso em: 04 jun. 2024.
APA
Santos, S. de S., Takahashi, D. Y., Sato, J. R., Ferreira, C. E., & Fujita, A. (2016). Statistical methods in graphs: parameter estimation, model selection, and hypothesis test. In Mathematical foundations and applications of graph entropy. Weinheim: Wiley-VCH. doi:10.1002/9783527693245.ch6
NLM
Santos S de S, Takahashi DY, Sato JR, Ferreira CE, Fujita A. Statistical methods in graphs: parameter estimation, model selection, and hypothesis test [Internet]. In: Mathematical foundations and applications of graph entropy. Weinheim: Wiley-VCH; 2016. [citado 2024 jun. 04 ] Available from: https://doi.org/10.1002/9783527693245.ch6
Vancouver
Santos S de S, Takahashi DY, Sato JR, Ferreira CE, Fujita A. Statistical methods in graphs: parameter estimation, model selection, and hypothesis test [Internet]. In: Mathematical foundations and applications of graph entropy. Weinheim: Wiley-VCH; 2016. [citado 2024 jun. 04 ] Available from: https://doi.org/10.1002/9783527693245.ch6
Artigo de periodico
Directed Transfer Function: Unified Asymptotic Theory and Some of Its Implications (2016)
Baccalá, Luiz Antonio ; Takahashi, Daniel Yasumasa; Sameshima, Koichi; Baccalá, Luiz Antonio
Source: IEEE Transactions on Biomedical Engineering. Unidade: EP
Subjects: NEUROCIÊNCIAS, PROCESSAMENTO DE SINAIS
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ABNT
BACCALÁ, Luiz Antonio et al. Directed Transfer Function: Unified Asymptotic Theory and Some of Its Implications. IEEE Transactions on Biomedical Engineering, 2016Tradução . . Disponível em: https://doi.org/10.1109/tbme.2016.2550199. Acesso em: 04 jun. 2024.
APA
Baccalá, L. A., Takahashi, D. Y., Sameshima, K., & Baccalá, L. A. (2016). Directed Transfer Function: Unified Asymptotic Theory and Some of Its Implications. IEEE Transactions on Biomedical Engineering. doi:10.1109/tbme.2016.2550199
NLM
Baccalá LA, Takahashi DY, Sameshima K, Baccalá LA. Directed Transfer Function: Unified Asymptotic Theory and Some of Its Implications [Internet]. IEEE Transactions on Biomedical Engineering. 2016 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.1109/tbme.2016.2550199
Vancouver
Baccalá LA, Takahashi DY, Sameshima K, Baccalá LA. Directed Transfer Function: Unified Asymptotic Theory and Some of Its Implications [Internet]. IEEE Transactions on Biomedical Engineering. 2016 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.1109/tbme.2016.2550199
Artigo de periodico
Identifying interacting pairs of sites in Ising models on a countable set (2015)
Galves, Antonio ; Orlandi, Enza; Takahashi, Daniel Yasumasa
Source: Brazilian Journal of Probability and Statistics. Unidade: IME
Subjects: MODELO DE ISING, PROBABILIDADE
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ABNT
GALVES, Antonio e ORLANDI, Enza e TAKAHASHI, Daniel Yasumasa. Identifying interacting pairs of sites in Ising models on a countable set. Brazilian Journal of Probability and Statistics, v. 29, n. 2, p. 443-459, 2015Tradução . . Disponível em: https://doi.org/10.1214/14-BJPS279. Acesso em: 04 jun. 2024.
APA
Galves, A., Orlandi, E., & Takahashi, D. Y. (2015). Identifying interacting pairs of sites in Ising models on a countable set. Brazilian Journal of Probability and Statistics, 29( 2), 443-459. doi:10.1214/14-BJPS279
NLM
Galves A, Orlandi E, Takahashi DY. Identifying interacting pairs of sites in Ising models on a countable set [Internet]. Brazilian Journal of Probability and Statistics. 2015 ; 29( 2): 443-459.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1214/14-BJPS279
Vancouver
Galves A, Orlandi E, Takahashi DY. Identifying interacting pairs of sites in Ising models on a countable set [Internet]. Brazilian Journal of Probability and Statistics. 2015 ; 29( 2): 443-459.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1214/14-BJPS279
Trabalho de evento
Partial directed coherence statistical performance characteristics in frequency domain (2015)
Sameshima, Koichi; Takahashi, Daniel Yasumasa; Baccalá, Luiz Antonio
Conference titles: Engineering in Medicine and Biology Society (EMBC) - Annual International Conference. Unidade: EP
Assunto: FREQUÊNCIA DE RESPOSTAS
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ABNT
SAMESHIMA, Koichi e TAKAHASHI, Daniel Yasumasa e BACCALÁ, Luiz Antonio. Partial directed coherence statistical performance characteristics in frequency domain. 2015, Anais.. New York: IEEE, 2015. Disponível em: https://doi.org/10.1109/EMBC.2015.7319609. Acesso em: 04 jun. 2024.
APA
Sameshima, K., Takahashi, D. Y., & Baccalá, L. A. (2015). Partial directed coherence statistical performance characteristics in frequency domain. In . New York: IEEE. doi:10.1109/EMBC.2015.7319609
NLM
Sameshima K, Takahashi DY, Baccalá LA. Partial directed coherence statistical performance characteristics in frequency domain [Internet]. 2015 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.1109/EMBC.2015.7319609
Vancouver
Sameshima K, Takahashi DY, Baccalá LA. Partial directed coherence statistical performance characteristics in frequency domain [Internet]. 2015 ;[citado 2024 jun. 04 ] Available from: https://doi.org/10.1109/EMBC.2015.7319609
Artigo de periodico
On the statistical performance of Granger-causal connectivity estimators (2015)
Sameshima, Koichi; Takahashi, Daniel Yasumasa; Baccalá, Luiz Antonio
Source: Brain Informatics. Unidades: EP, FM
Assunto: RESSONÂNCIA MAGNÉTICA
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ABNT
SAMESHIMA, Koichi e TAKAHASHI, Daniel Yasumasa e BACCALÁ, Luiz Antonio. On the statistical performance of Granger-causal connectivity estimators. Brain Informatics, v. 2, p. 119-133, 2015Tradução . . Disponível em: https://doi.org/10.1007/s40708-015-0015-1. Acesso em: 04 jun. 2024.
APA
Sameshima, K., Takahashi, D. Y., & Baccalá, L. A. (2015). On the statistical performance of Granger-causal connectivity estimators. Brain Informatics, 2, 119-133. doi:10.1007/s40708-015-0015-1
NLM
Sameshima K, Takahashi DY, Baccalá LA. On the statistical performance of Granger-causal connectivity estimators [Internet]. Brain Informatics. 2015 ; 2 119-133.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1007/s40708-015-0015-1
Vancouver
Sameshima K, Takahashi DY, Baccalá LA. On the statistical performance of Granger-causal connectivity estimators [Internet]. Brain Informatics. 2015 ; 2 119-133.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1007/s40708-015-0015-1
Artigo de periodico
A comparative study of statistical methods used to identify dependencies between gene expression signals (2014)
Santos, Suzana de Siqueira ; Takahashi, Daniel Yasumasa ; Nakata, Asuka; Fujita, André
Source: Briefings in Bioinformatics. Unidade: IME
Subjects: BIOINFORMÁTICA, ESTATÍSTICA COMPUTACIONAL, CORRELAÇÃO GENÉTICA E AMBIENTAL
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ABNT
SANTOS, Suzana de Siqueira et al. A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, v. 15, n. 6, p. 906-918, 2014Tradução . . Disponível em: https://doi.org/10.1093/bib/bbt051. Acesso em: 04 jun. 2024.
APA
Santos, S. de S., Takahashi, D. Y., Nakata, A., & Fujita, A. (2014). A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, 15( 6), 906-918. doi:10.1093/bib/bbt051
NLM
Santos S de S, Takahashi DY, Nakata A, Fujita A. A comparative study of statistical methods used to identify dependencies between gene expression signals [Internet]. Briefings in Bioinformatics. 2014 ; 15( 6): 906-918.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1093/bib/bbt051
Vancouver
Santos S de S, Takahashi DY, Nakata A, Fujita A. A comparative study of statistical methods used to identify dependencies between gene expression signals [Internet]. Briefings in Bioinformatics. 2014 ; 15( 6): 906-918.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1093/bib/bbt051
Artigo de periodico
Canonical information flow decomposition among neural structure subsets (2014)
Takahashi, Daniel Yasumasa ; Baccalá, Luiz Antonio ; Sameshima, Koichi
Source: Frontiers in Neuroinformatics. Unidades: EP, FM
Subjects: NEURÔNIOS (ANATOMIA;FISIOLOGIA), NEUROCIÊNCIAS, INFORMAÇÃO, TEORIA DA INFORMAÇÃO
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ABNT
TAKAHASHI, Daniel Yasumasa e BACCALÁ, Luiz Antonio e SAMESHIMA, Koichi. Canonical information flow decomposition among neural structure subsets. Frontiers in Neuroinformatics, v. 8, p. 49, 2014Tradução . . Disponível em: https://doi.org/10.3389/fninf.2014.00049. Acesso em: 04 jun. 2024.
APA
Takahashi, D. Y., Baccalá, L. A., & Sameshima, K. (2014). Canonical information flow decomposition among neural structure subsets. Frontiers in Neuroinformatics, 8, 49. doi:10.3389/fninf.2014.00049
NLM
Takahashi DY, Baccalá LA, Sameshima K. Canonical information flow decomposition among neural structure subsets [Internet]. Frontiers in Neuroinformatics. 2014 ; 8 49.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fninf.2014.00049
Vancouver
Takahashi DY, Baccalá LA, Sameshima K. Canonical information flow decomposition among neural structure subsets [Internet]. Frontiers in Neuroinformatics. 2014 ; 8 49.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fninf.2014.00049
Artigo de periodico
Canonical information flow decomposition among neural structure subsets (2014)
Takahashi, Daniel Yasumasa ; Sameshima, Koichi ; Baccalá, Luiz Antonio
Source: Frontiers in Neuroinformatics. Unidades: EP, FM, BIOINFORMÁTICA
Subjects: PROCESSAMENTO DE SINAIS, NEUROCIÊNCIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAKAHASHI, Daniel Yasumasa e SAMESHIMA, Koichi e BACCALÁ, Luiz Antonio. Canonical information flow decomposition among neural structure subsets. Frontiers in Neuroinformatics, v. 8, p. 1-11, 2014Tradução . . Disponível em: https://doi.org/10.3389/fninf.2014.00049. Acesso em: 04 jun. 2024.
APA
Takahashi, D. Y., Sameshima, K., & Baccalá, L. A. (2014). Canonical information flow decomposition among neural structure subsets. Frontiers in Neuroinformatics, 8, 1-11. doi:10.3389/fninf.2014.00049
NLM
Takahashi DY, Sameshima K, Baccalá LA. Canonical information flow decomposition among neural structure subsets [Internet]. Frontiers in Neuroinformatics. 2014 ; 8 1-11.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fninf.2014.00049
Vancouver
Takahashi DY, Sameshima K, Baccalá LA. Canonical information flow decomposition among neural structure subsets [Internet]. Frontiers in Neuroinformatics. 2014 ; 8 1-11.[citado 2024 jun. 04 ] Available from: https://doi.org/10.3389/fninf.2014.00049
Artigo de periodico
A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data (2014)
Fujita, André ; Takahashi, Daniel Yasumasa ; Patriota, Alexandre Galvão ; Sato, João Ricardo
Source: Statistics in Medicine. Unidade: IME
Subjects: RECONHECIMENTO DE PADRÕES, INTELIGÊNCIA ARTIFICIAL, ESTATÍSTICA COMPUTACIONAL, RESSONÂNCIA MAGNÉTICA, INFERÊNCIA NÃO PARAMÉTRICA, INFERÊNCIA ESTATÍSTICA, COMPUTAÇÃO GRÁFICA
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ABNT
FUJITA, André et al. A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data. Statistics in Medicine, v. 33, n. 28, p. 4949-4962, 2014Tradução . . Disponível em: https://doi.org/10.1002/sim.6292. Acesso em: 04 jun. 2024.
APA
Fujita, A., Takahashi, D. Y., Patriota, A. G., & Sato, J. R. (2014). A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data. Statistics in Medicine, 33( 28), 4949-4962. doi:10.1002/sim.6292
NLM
Fujita A, Takahashi DY, Patriota AG, Sato JR. A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data [Internet]. Statistics in Medicine. 2014 ; 33( 28): 4949-4962.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1002/sim.6292
Vancouver
Fujita A, Takahashi DY, Patriota AG, Sato JR. A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging data [Internet]. Statistics in Medicine. 2014 ; 33( 28): 4949-4962.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1002/sim.6292
Artigo de periodico
A non-parametric method to estimate the number of clusters (2014)
Fujita, André ; Takahashi, Daniel Yasumasa ; Patriota, Alexandre Galvão
Source: Computational Statistics & Data Analysis. Unidade: IME
Subjects: BIOINFORMÁTICA, ESTATÍSTICA COMPUTACIONAL, ANÁLISE DE CONGLOMERADOS, ANÁLISE ESPECTRAL (ANÁLISE DE SÉRIES TEMPORAIS), HEURÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FUJITA, André e TAKAHASHI, Daniel Yasumasa e PATRIOTA, Alexandre Galvão. A non-parametric method to estimate the number of clusters. Computational Statistics & Data Analysis, v. 73, p. 27-39, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.csda.2013.11.012. Acesso em: 04 jun. 2024.
APA
Fujita, A., Takahashi, D. Y., & Patriota, A. G. (2014). A non-parametric method to estimate the number of clusters. Computational Statistics & Data Analysis, 73, 27-39. doi:10.1016/j.csda.2013.11.012
NLM
Fujita A, Takahashi DY, Patriota AG. A non-parametric method to estimate the number of clusters [Internet]. Computational Statistics & Data Analysis. 2014 ; 73 27-39.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1016/j.csda.2013.11.012
Vancouver
Fujita A, Takahashi DY, Patriota AG. A non-parametric method to estimate the number of clusters [Internet]. Computational Statistics & Data Analysis. 2014 ; 73 27-39.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1016/j.csda.2013.11.012
Artigo de periodico
Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders (2013)
Sato, João Ricardo ; Takahashi, Daniel Yasumasa ; Hoexter, Marcelo Queiroz ; Massirer, Katlin Brauer ; Fujita, André
Source: Neuroimage. Unidades: IME, FM
Assunto: DISTÚRBIOS PSICOLÓGICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SATO, João Ricardo et al. Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders. Neuroimage, v. 77, p. 44-51, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.neuroimage.2013.03.035. Acesso em: 04 jun. 2024.
APA
Sato, J. R., Takahashi, D. Y., Hoexter, M. Q., Massirer, K. B., & Fujita, A. (2013). Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders. Neuroimage, 77, 44-51. doi:10.1016/j.neuroimage.2013.03.035
NLM
Sato JR, Takahashi DY, Hoexter MQ, Massirer KB, Fujita A. Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders [Internet]. Neuroimage. 2013 ; 77 44-51.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1016/j.neuroimage.2013.03.035
Vancouver
Sato JR, Takahashi DY, Hoexter MQ, Massirer KB, Fujita A. Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders [Internet]. Neuroimage. 2013 ; 77 44-51.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1016/j.neuroimage.2013.03.035
Artigo de periodico
Discriminating different classes of biological networks by analyzing the graphs spectra distribution (2012)
Takahashi, Daniel Yasumasa ; Sato, João Ricardo ; Ferreira, Carlos Eduardo ; Fujita, André
Source: PLOS ONE. Unidade: IME
Assunto: COMBINATÓRIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAKAHASHI, Daniel Yasumasa et al. Discriminating different classes of biological networks by analyzing the graphs spectra distribution. PLOS ONE, v. 7, n. 12, p. 1-12, 2012Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0049949. Acesso em: 04 jun. 2024.
APA
Takahashi, D. Y., Sato, J. R., Ferreira, C. E., & Fujita, A. (2012). Discriminating different classes of biological networks by analyzing the graphs spectra distribution. PLOS ONE, 7( 12), 1-12. doi:10.1371/journal.pone.0049949
NLM
Takahashi DY, Sato JR, Ferreira CE, Fujita A. Discriminating different classes of biological networks by analyzing the graphs spectra distribution [Internet]. PLOS ONE. 2012 ; 7( 12): 1-12.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1371/journal.pone.0049949
Vancouver
Takahashi DY, Sato JR, Ferreira CE, Fujita A. Discriminating different classes of biological networks by analyzing the graphs spectra distribution [Internet]. PLOS ONE. 2012 ; 7( 12): 1-12.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1371/journal.pone.0049949

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