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 ====== Publication List ======
-  - Fujita A, Kojima, K, Patriota AG, Sato JR, Severino P, Miyano S. A fast and robust statistical test based on Likelihood ratio with Bartlett correction to identify Granger causality between gene sets. Bioinformatics (accepted).
+  - Kasparek T, Thomaz CE, Sato JR, Schwarz D, Janousova E,Marecek R, Prikryl R, Vanicek J, Fujita A, Ceskova E. Maximum-uncertainty linear discrimination analysis of first-episode schizophrenia subjects. Psychiatry Research: Neuroimaging. 2011 (in press).
-  - Fujita A, Severino P, Sato JR, Miyano S. Granger causality in systems biology: modeling gene networks in time series microarray data using vector autoregressive models. Lecture Notes in Bioinformatics (accepted).
+  - Niida A, Imoto S, Yamaguchi R, Nagasaki M, Fujita A, Shimamura T, Miyano S. Model-free unsupervised gene set screening based on information enrichment in expression profiles. Bioinformatics.　26:3090-3097, 2010.
-  - Sato JR, Fujita A, Cardoso EF, Thomaz CE, Brammer MJ, Amaro Jr E. Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis. NeuroImage (accepted).
+  - Fujita A, Kojima, K, Patriota AG, Sato JR, Severino P, Miyano S. A fast and robust statistical test based on Likelihood ratio with Bartlett correction to identify Granger causality between gene sets. Bioinformatics. 26:2349-2351, 2010.
-  - Shimamura T, Imoto S, Nagasaki M, Yamauchi M, Yamaguchi R, Fujita A, Tamada Y, Gotoh N, Miyano S. Collocation-based sparse estimation for constructing dynamic gene networks. Genome Informatics (accepted).
+  - Fujita A, Severino P, Sato JR, Miyano S. Granger causality in systems biology: modeling gene networks in time series microarray data using vector autoregressive models. Lecture Notes in Bioinformatics. 6268:13-24, 2010.
-  - Fujita A, Nagasaki, M, Imoto S, Saito A, Ikeda E, Shimamura T, Yamaguchi R, Hayashizaki Y, Miyano S. Comparison of gene expression profiles produced by CAGE, illumina microarray and Real Time RT-PCR. Genome Informatics (accepted).
+  - Sato JR, Fujita A, Cardoso EF, Thomaz CE, Brammer MJ, Amaro Jr E. Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis. NeuroImage. 52:1444-1455, 2010.
-  - Fujita A, Sato JR, Kojima K, Gomes LR, Nagasaki M, Sogayar MC, Miyano S. Identification of Granger causality between gene sets. Journal of Bioinformatics and Computational Biology (accepted).
+  - Shimamura T, Imoto S, Nagasaki M, Yamauchi M, Yamaguchi R, Fujita A, Tamada Y, Gotoh N, Miyano S. Collocation-based sparse estimation for constructing dynamic gene networks. Genome Informatics. 24:164-178, 2010.
+  - Fujita A, Nagasaki, M, Imoto S, Saito A, Ikeda E, Shimamura T, Yamaguchi R, Hayashizaki Y, Miyano S. Comparison of gene expression profiles produced by CAGE, illumina microarray and Real Time RT-PCR. Genome Informatics. 24:56-68, 2010.
+  - Fujita A, Sato JR, Kojima K, Gomes LR, Nagasaki M, Sogayar MC, Miyano S. Identification of Granger causality between gene sets. Journal of Bioinformatics and Computational Biology. 8:679-701, 2010.
   - Fujita A, Patriota AG, Sato JR, Miyano S. The impact of measurement error in the identification of regulatory networks. BMC Bioinformatics. 10:412, 2009.
   - Fujita A, Sato JR, da Silva FHL, Galvao MC, Sogayar MC, Miyano S. Quality control and reproducibility in DNA microarray experiments. Genome Informatics. 23:21-31, 2009.