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+====== Book chapter ======
+  - Fujita A, Sato JR, Demasi MAA, Miyano S, Sogayar MC, Ferreira CE. An introduction to time-varying connectivity estimation for gene regulatory networks. In: Frank Emmert-Streib; Matthias Dehmer. (Org.). Medical Biostatistics for complex diseases. Weinheim, Germany: Wiley VCH Verlag, p.205-230, 2010.
 ====== Publication List ======
-  - 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).
+  - 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).
-  - 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).
+  - 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.
-  - 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).
+  - 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.
-  - 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).
+  - 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.
+  - 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.
+  - 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.
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   - Fujita A, Sato JR, Rodrigues LO, Ferreira MC, Sogayar MC. Evaluating different methods of microarray data normalization. BMC Bioinformatics 7:469, 2006.
   - Fujita A, Massirer KB, Durham AM, Ferreira CE, Sogayar MC. The GATO gene annotation tool for research laboratories. Brazilian Journal of Medical and Biological Research 38:1571-1574, 2005.