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André Fujita

Showing results (1-10 of 72) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|June 15, 2014
A tutorial to identify nonlinear associations in gene expression time series dataAndré Fujita, Satoru Miyano
Frontiers in Neuroscience|March 7, 2017
A Statistical Method to Distinguish Functional Brain NetworksAndré Fujita, Maciel C Vidal, Daniel Y Takahashi
Genetics and Molecular Biology|September 6, 2019
Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancerFernando Andrade, Asuka Nakata, Noriko Gotoh, et al.
Frontiers in Neuroscience|April 17, 2023
Spectral density-based clustering algorithms for complex networksTaiane Coelho Ramos, Janaina Mourão-Miranda, André Fujita
Genome Informatics. International Conference on Genome Informatics|May 9, 2009
Estimation of nonlinear gene regulatory networks via L1 regularized NVAR from time series gene expression dataKaname Kojima, André Fujita, Teppei Shimamura, et al.
Journal of Psychiatry & Neuroscience : JPN|October 28, 2015
Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysisJoão Ricardo Sato, Joana Balardin, Maciel Calebe Vidal, et al.
BMC Bioinformatics|December 17, 2009
The impact of measurement errors in the identification of regulatory networksAndré Fujita, Alexandre G Patriota, João R Sato, et al.
Statistics in Medicine|September 5, 2014
A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging dataAndré Fujita, Daniel Y Takahashi, Alexandre G Patriota, et al.
BMC Bioinformatics|November 21, 2007
GEDI: a user-friendly toolbox for analysis of large-scale gene expression dataAndré Fujita, João R Sato, Carlos E Ferreira, et al.
Briefings in Bioinformatics|August 22, 2013
A comparative study of statistical methods used to identify dependencies between gene expression signalsSuzana de Siqueira Santos, Daniel Yasumasa Takahashi, Asuka Nakata, et al.
Pageof 8

Showing results (1-10 of 72) with videos related to

Sort By:
Pageof 8
Methods in Molecular Biology (Clifton, N.J.)|June 15, 2014
A tutorial to identify nonlinear associations in gene expression time series dataAndré Fujita, Satoru Miyano
Frontiers in Neuroscience|March 7, 2017
A Statistical Method to Distinguish Functional Brain NetworksAndré Fujita, Maciel C Vidal, Daniel Y Takahashi
Genetics and Molecular Biology|September 6, 2019
Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancerFernando Andrade, Asuka Nakata, Noriko Gotoh, et al.
Frontiers in Neuroscience|April 17, 2023
Spectral density-based clustering algorithms for complex networksTaiane Coelho Ramos, Janaina Mourão-Miranda, André Fujita
Genome Informatics. International Conference on Genome Informatics|May 9, 2009
Estimation of nonlinear gene regulatory networks via L1 regularized NVAR from time series gene expression dataKaname Kojima, André Fujita, Teppei Shimamura, et al.
Journal of Psychiatry & Neuroscience : JPN|October 28, 2015
Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysisJoão Ricardo Sato, Joana Balardin, Maciel Calebe Vidal, et al.
BMC Bioinformatics|December 17, 2009
The impact of measurement errors in the identification of regulatory networksAndré Fujita, Alexandre G Patriota, João R Sato, et al.
Statistics in Medicine|September 5, 2014
A non-parametric statistical test to compare clusters with applications in functional magnetic resonance imaging dataAndré Fujita, Daniel Y Takahashi, Alexandre G Patriota, et al.
BMC Bioinformatics|November 21, 2007
GEDI: a user-friendly toolbox for analysis of large-scale gene expression dataAndré Fujita, João R Sato, Carlos E Ferreira, et al.
Briefings in Bioinformatics|August 22, 2013
A comparative study of statistical methods used to identify dependencies between gene expression signalsSuzana de Siqueira Santos, Daniel Yasumasa Takahashi, Asuka Nakata, et al.
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