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André Fujita
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2020 – today
- 2023
- [j37]Grover E. C. Guzman
, André Fujita:
A fast algorithm to approximate the spectral density of locally tree-like networks with assortativity. J. Complex Networks 11(2) (2023) - [j36]Carlos E. M. Relvas, Asuka Nakata, Guoan Chen, David G. Beer, Noriko Gotoh, André Fujita
A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification. J. Bioinform. Comput. Biol. 21(4): 2350019:1-2350019:26 (2023) - [c4]Victor Chavauty Villela, Eduardo Silva Lira, André Fujita:
Spectrum-Based Statistical Methods for Directed Graphs with Applications in Biological Data. BSB 2023: 46-57 - 2022
- [j35]Grover E. C. Guzman
A fast parameter estimator for large complex networks. J. Complex Networks 10(3) (2022) - [j34]Grover E. C. Guzman
Efficient eigenvalue counts for tree-like networks. J. Complex Networks 10(5) (2022) - [j33]Amanda Yumi Ambriola Oku
Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms. Frontiers Comput. Neurosci. 16 (2022) - 2021
- [j32]Suzana de Siqueira Santos
Spectral density of random graphs: convergence properties and application in model fitting. J. Complex Networks 9(6) (2021) - [j31]Adèle Helena Ribeiro
Granger Causality among Graphs and Application to Functional Brain Connectivity in Autism Spectrum Disorder. Entropy 23(9): 1204 (2021) - [j30]Grover E. C. Guzman
Convolution-based linear discriminant analysis for functional data classification. Inf. Sci. 581: 469-478 (2021) - [j29]Grover E. C. Guzman
Efficient Laplacian spectral density computations for networks with arbitrary degree distributions. Netw. Sci. 9(3): 312-327 (2021) - [c3]Renata B. Biazzi
Predicting soft robot's locomotion fitness. GECCO Companion 2021: 81-82 - 2020
- [j28]André Fujita, Eduardo Silva Lira, Suzana de Siqueira Santos
A semi-parametric statistical test to compare complex networks. J. Complex Networks 8(2) (2020) - [i2]Carlos E. M. Relvas, André Fujita:
Stage I non-small cell lung cancer stratification by using a model-based clustering algorithm with covariates. CoRR abs/2004.02333 (2020)
2010 – 2019
- 2018
- [j27]João Ricardo Sato
Complex Network Measures in Autism Spectrum Disorders. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 581-587 (2018) - 2017
- [j26]André Fujita
Correlation between graphs with an application to brain network analysis. Comput. Stat. Data Anal. 109: 76-92 (2017) - 2016
- [c2]Abner Cardoso Rodrigues
Source and sink nodes in absence seizures. EMBC 2016: 2814-2817 - 2014
- [j25]Suzana de Siqueira Santos
A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings Bioinform. 15(6): 906-918 (2014) - [j24]André Fujita, Daniel Yasumasa Takahashi, Alexandre Galvão Patriota
A non-parametric method to estimate the number of clusters. Comput. Stat. Data Anal. 73: 27-39 (2014) - 2013
- [j23]Masao Nagasaki
XiP: a computational environment to create, extend and share workflows. Bioinform. 29(1): 137-139 (2013) - [j22]João Ricardo Sato
Measuring network's entropy in ADHD: A new approach to investigate neuropsychiatric disorders. NeuroImage 77: 44-51 (2013) - 2012
- [j21]Kaname Kojima, Seiya Imoto, Rui Yamaguchi, André Fujita, Mai Yamauchi, Noriko Gotoh
Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing. BMC Genom. 13(S-1): S6 (2012) - [j20]André Fujita, Patricia Severino
Functional clustering of time series gene expression data by Granger causality. BMC Syst. Biol. 6: 137 (2012) - [i1]Daniel Yasumasa Takahashi, João Ricardo Sato, Carlos Eduardo Ferreira, André Fujita:
Discriminating different classes of biological networks by analyzing the graphs spectra distribution. CoRR abs/1208.2976 (2012) - 2011
- [j19]Masao Nagasaki
Systems biology model repository for macrophage pathway simulation. Bioinform. 27(11): 1591-1593 (2011) - [j18]André Fujita, João Ricardo Sato
Inferring Contagion in Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 8(2): 570-576 (2011) - 2010
- [j17]André Fujita, Kaname Kojima, Alexandre Galvão Patriota
A fast and robust statistical test based on likelihood ratio with Bartlett correction to identify Granger causality between gene sets. Bioinform. 26(18): 2349-2351 (2010) - [j16]Atsushi Niida, Seiya Imoto, Rui Yamaguchi, Masao Nagasaki
Model-free unsupervised gene set screening based on information enrichment in expression profiles. Bioinform. 26(24): 3090-3097 (2010) - [j15]André Fujita, João Ricardo Sato, Kaname Kojima, Luciana Rodrigues Gomes, Masao Nagasaki, Mari Cleide Sogayar
Identification of Granger Causality between Gene Sets. J. Bioinform. Comput. Biol. 8(4): 679-701 (2010) - [j14]João Ricardo Sato
Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for fMRI data analysis. NeuroImage 52(4): 1444-1455 (2010) - [c1]André Fujita, Patricia Severino
Granger Causality in Systems Biology: Modeling Gene Networks in Time Series Microarray Data Using Vector Autoregressive Models. BSB 2010: 13-24
2000 – 2009
- 2009
- [j13]André Fujita, Alexandre Galvão Patriota
The impact of measurement errors in the identification of regulatory networks. BMC Bioinform. 10: 412 (2009) - [j12]Teppei Shimamura
Recursive regularization for inferring gene networks from time-course gene expression profiles. BMC Syst. Biol. 3: 41 (2009) - [j11]André Fujita, João Ricardo Sato
Comparing Pearson, Spearman and Hoeffding's d Measure for Gene Expression Association Analysis. J. Bioinform. Comput. Biol. 7(4): 663-684 (2009) - [j10]João Ricardo Sato
Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction. NeuroImage 46(1): 105-114 (2009) - [j9]João Ricardo Sato, André Fujita, Carlos Eduardo Thomaz
Corrigendum to "Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction": [NeuroImage 46 (2009) 105-114]. NeuroImage 47(1): 423-425 (2009) - 2008
- [j8]André Fujita, Luciana Rodrigues Gomes, João Ricardo Sato
Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates. BMC Syst. Biol. 2: 106 (2008) - [j7]André Fujita, João Ricardo Sato
Modeling Nonlinear Gene Regulatory Networks from Time Series Gene Expression Data. J. Bioinform. Comput. Biol. 6(5): 961-979 (2008) - [j6]João Ricardo Sato
Hyperplane navigation: A method to set individual scores in fMRI group datasets. NeuroImage 42(4): 1473-1480 (2008) - 2007
- [j5]João Ricardo Sato
DWT-CEM: an algorithm for scale-temporal clustering in fMRI. Biol. Cybern. 97(1): 33-45 (2007) - [j4]André Fujita, João Ricardo Sato
Time-varying modeling of gene expression regulatory networks using the wavelet dynamic vector autoregressive method. Bioinform. 23(13): 1623-1630 (2007) - [j3]André Fujita, João Ricardo Sato
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data. BMC Bioinform. 8 (2007) - [j2]André Fujita, João Ricardo Sato
Modeling gene expression regulatory networks with the sparse vector autoregressive model. BMC Syst. Biol. 1: 39 (2007) - 2006
- [j1]André Fujita, João Ricardo Sato
Evaluating different methods of microarray data normalization. BMC Bioinform. 7: 469 (2006)
Coauthor Index
aka: João Ricardo Sato
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