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Book chapters

[B1] S. Imoto, H. Matsuno and S. Miyano (2005) Gene Networks: Estimation, Modeling and Simulation. in R. Eils and A. Kriete (Eds.), Computational Systems Biology, Academic Press, 205-228.

[B2] S. Imoto, Y. Tamada and C.J. Savoie and S. Miyano (2006) Analysis of Gene Networks for Drug Target Discovery and Validation. in J. Walker and M. Sioud (Eds.), Target Discovery and Validation, Volume 1, pp.33-56 (a volume of "Methods in Molecular Biology" series), Humana Press, USA.

[B3] S. Imoto and S. Miyano (2007) Bayesian Network Approach to Estimate Gene Networks. in A. Mittal, A. Kassim and T. Tan (Eds.), Bayesian Network Technologies: Applications and Graphical Models, Idea Group Publishers, USA. pp.269-299. (Refereed book chapter)

[B4] S. Imoto, Y. Tamada, H. Araki and S. Miyano (2010) Computational Drug Target Pathway Discovery: A Bayesian Network Approach. in H. Lu, B. Schokop, H. Zhao (Eds.), Handbook of Computational Statistics: Statistical Bioinformatics, Springer-Varlag. in press.

Journal papers and refereed proceedings (peer reviewed)

[J1] S. Imoto and S. Konishi (1999). Nonlinear regression models using B-spline and information criteria (in Japanese with English abstract). Proc. Inst. Statist. Math., 47, 359-373. PDF(878KB)

[J2] S. Imoto and S. Konishi (1999). Estimation of B-spline nonlinear regression models using information criteria (in Japanese). Jap. J. Appl. Statist., 28, 137-150.

[J3] T. Ando, S. Imoto and S. Konishi (2001). Estimating nonlinear regression models based on radial basis function networks (in Japanese with English abstract). Jap. J. Appl. Statist., 30, 19-35.

[J4] S. Imoto, T. Goto and S. Miyano (2002). Estimation of genetic networks and functional structures between genes by using Bayesian network and nonparametric regression. Pacific Symposium on Biocomputing, 7, 175-186. (PSB2002: Refereed conference). PDF(403KB)

[J5] S. Imoto, S. Kim, T. Goto, S. Aburatani, K. Tashiro, S. Kuhara and S. Miyano (2002). Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. Proc. 1st IEEE Computer Society Bioinformatics Conference, 219-227. (CSB2002: Refereed conference). (The number of accepted papers is 19 out of 103 submissions). (This paper was selected as one of the 10 best papers). PDF(244KB)

[J6] M.J.L. de Hoon, S. Imoto and S. Miyano (2002). Statistical analysis of a small set of time-ordered gene expression data using linear splines. Bioinformatics, 18, 1477-1485. PDF(138KB)

[J7] M.J.L. de Hoon, S. Imoto and S. Miyano (2002). Inferring gene regulatory networks from time-ordered gene expression data using differential equations. Proc. 5th International Conference on Discovery Science, Lecture Note in Artificial Intelligence, 2534, 267-274, Springer-Verlag. (DS2002: Refereed conference). PDF(128KB)

[J8] M.J.L. de Hoon, S. Imoto, K. Kobayashi, N. Ogasawara and S. Miyano (2003). Inferring gene regulatory networks from time-ordered gene expression data of Bacillus subtilis using differential equations. Pacific Symposium on Biocomputing, 8, 17-28. (PSB2003: Refereed conference). PDF(166KB)

[J9] S. Kim, S. Imoto and S. Miyano (2003). Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data. Proc. 1st Computational Methods in Systems Biology, Lecture Note in Computer Science, 2602, 104-113, Springer-Verlag. (CMSB2003: Refereed conference). (The number of accepted papers is 11 out of 39 submissions). PDF(179KB)

[J10] S. Imoto, S. Kim, T. Goto, S. Aburatani, K. Tashiro, S. Kuhara and S. Miyano (2003). Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. Journal of Bioinformatics and Computational Biology, 1(2), 231-252. (This paper is an extend version of CSB2002 paper [J5]). PDF(751KB)

[J11] C.J. Savoie, S. Aburatani, S. Watanabe, Y. Eguchi, S. Muta, S. Imoto, S. Miyano, S. Kuhara and K. Tashiro (2003). Use of gene networks from full genome microarray libraries to identify functionally relevant drug-affected genes and gene regulation cascades. DNA Research, 10, 19-25. PDF(656KB)

[J12] S. Imoto and S. Konishi (2003). Selection of smoothing parameters in B-spline nonparametric regression models using information criteria. Annals of the Institute of Statistical Mathematics, 55(4), 671-687.

[J13] Y. Tamada, S. Kim, H. Bannai, S. Imoto, K. Tashiro, S. Kuhara and S. Miyano (2003). Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection. Bioinformatics, 19 Suppl.2, ii227-ii236. (ECCB2003: Refereed conference). (The number of accepted paper is 27 out of 124 submissions). PDF(172KB)

[J14] M.J.L. de Hoon, S. Ott, S. Imoto and S. Miyano (2003). Validation of noisy dynamical system models of gene regulation inferred from time-course gene expression data at arbitrary time intervals. Proc. 2nd European Conference on Computational Biology, 26-28. (ECCB2003: Refereed conference). (The number of accepted paper is 15 out of 117 submissions). PDF(105KB)

[J15] S. Imoto, T. Higuchi, T. Goto, K. Tashiro, S. Kuhara and S. Miyano (2003). Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks. Proc. 2nd Computational Systems Bioinformatics, 104-113. (CSB2003: Refereed conference). (The number of accepted papers is 28 out of 151 submissions). (This paper was selected as one of the 10 best papers). PDF(232KB)

[J16] S. Imoto*, C.J. Savoie*, S. Aburatani*, S. Kim, K. Tashiro, S. Kuhara and S. Miyano (2003). Use of gene networks for identifying and validating drug targets. Journal of Bioinformatics and Computational Biology, 1(3), 459-474. PDF(1640KB) (*These authors equally contributed to this work).

[J17] S. Kim, S. Imoto and S. Miyano (2003). Inferring gene networks from time series microarray data using dynamic Bayesian networks. Briefings in Bioinformatics, 4(3), 228-235.

[J18] S. Konishi, T. Ando and S. Imoto (2004). Bayesian information criteria and smoothing parameter selection in radial basis function networks. Biometrika, 91(1), 27-43.

[J19] M.J.L. de Hoon, S. Imoto, J. Nolan and S. Miyano (2004). Open source clustering software. Bioinformatics, 20(9), 1453-1454. PDF(53KB)

[J20] M.J.L. de Hoon, S. Imoto, K. Kobayashi, N. Ogasawara and S. Miyano (2004). Predicting the operon structure of Bacillus subtilis using operon length, intergene distance, and gene expression information. Pacific Symposium on Biocomputing, 9, 276-287. (PSB2004: Refereed conference). PDF(229KB)

[J21] N. Nariai, S. Kim, S. Imoto and S. Miyano (2004). Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks. Pacific Symposium on Biocomputing, 9, 336-347. (PSB2004: Refereed conference). PDF(242KB)

[J22] S. Ott, S. Imoto and S. Miyano (2004). Finding optimal models for small gene networks. Pacific Symposium on Biocomputing, 9, 557-567. (PSB2004: Refereed conference). PDF(113KB)

[J23] S. Kim, S. Imoto and S. Miyano. (2004). Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data. Biosystems, 75(1-3), 57-65. (This paper is an extension version of CMSB2003 paper [J9]). PDF(311KB)

[J24] S. Imoto, T. Higuchi, T. Goto, K. Tashiro, S. Kuhara and S. Miyano (2004). Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks. Journal of Bioinformatics and Computational Biology, 2(1), 77-98. (This paper is an extend version of CSB2003 paper [J15]). PDF(336KB)

[J25] R. Nakamichi, S. Imoto and S. Miyano. (2004). Case-control study of binary trait considering interactions between SNPs and environmental effects using logistic regression. Proc. 4th IEEE Bioinformatics and Bioengineering, 73-78. (BIBE2004: Refereed conference).

[J26] M.J.L. de Hoon, Y. Makita, S. Imoto, K. Kobayashi, N. Ogasawara, K. Nakai and S. Miyano. (2004). Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data. Bioinformatics, 20 Suppl.1, i101-i108. (ISMB/ECCB2004: Refereed conference). (The number of accepted papers is 50 out of 492 submissions).PDF(89KB)

[J27] Y. Araki, S. Konishi and S. Imoto. (2004). Functional discriminant analysis for time-seriese gene expression data via radial basis function expansion. Proc. COMPSTAT 2004, 613-620, Physica-Verlag/Springer. (COMPSTAT2004: Refereed conference). PDF(147KB)

[J28] S. Imoto*, T. Higuchi*, S. Kim, E. Jeong and S. Miyano. (2004). Residual bootstrapping and median filtering for robust estimation of gene networks from microarray data. Proc. 2nd Computational Methods in Systems Biology, Lecture Note in Bioinformatics, 3082, 149-160, Springer-Verlag. (CMSB2004: Refereed conference). (*These authors equally contributed to this work). PDF(291KB)

[J29] R. Yoshida, T. Higuchi and S. Imoto. (2004). A mixed factors model for dimension reduction and extraction of a group structure in gene expression data. Proc. 3rd Computational Systems Bioinformatics, 161-172. (CSB2004: Refereed conference). (The number of accepted papers is 30 out of 202 submissions). PDF(498KB)

[J30] T. Ando, S. Imoto and S. Miyano (2004). Functional data analysis of the dynamics of gene regulatory networks. Proc. Knowledge Exploration in Life Science Informatics, Lecture Note in Computer Science, 3303, 69-83, Springer-Verlag. (KELSI2004: Refereed conference).

[J31] T. Ando, S. Imoto and S. Miyano (2004). Kernel mixture survival models for identifying cancer subtypes, predicting patient's cancer types and survival probabilities. Genome Informatics, 15(2), 201-210. (GIW2004: Refereed conference).

[J32] T. Ando, S. Imoto and S. Konishi. (2004). Adaptive learning machines for nonlinear classification and Bayesian information criterion. Bulletin of Informatics and Cybernetics, 36, 147-162.

[J33] R. Yoshida, S. Imoto and T. Higuchi. (2005). A penalized likelihood estimation on transcriptional module-based clustering. Proc. 1st International Workshop on Data Mining and Bioinformatics, Lecture Note in Comupter Science, 3482, 389-401, Springer-Verlag. (DMBio2005: Refereed conference).

[J34] O. Hirose, N. Nariai, Y. Tamada, H. Bannai, S. Imoto and S. Miyano. (2005). Estimating gene networks from expression data and binding location data via boolean networks. Proc. 1st International Workshop on Data Mining and Bioinformatics, Lecture Note in Computer Science, 3482, 349-356, Springer-Verlag. (DMBio2005: Refereed conference).

[J35] Y. Tamada, H. Bannai, S. Imoto, T. Katayama, M. Kanehisa and S. Miyano. (2005). Utilizing evolutionary information and gene expression data for estimating gene regulations with Bayesian network models. Journal of Bioinformatics and Computational Biology, 3(6), 1295-1313. PDF(624KB)

[J36] R. Yoshida, S. Imoto and T. Higuchi. (2005). Estimating time-dependent gene networks from time series microarray data by dynamic linear models with Markov switching. Proc. 4th Computational Systems Bioinformatics, 289-298. (CSB2005: Refereed conference). (The number of accepted papers is 30 out of 246 submissions). PDF(988KB)

[J37] Y. Tamada, S. Imoto, K. Tashiro, S. Kuhara and S. Miyano. (2005). Identifying drug active pathways from gene networks estimated by gene expression data. Genome Informatics, 16(1), 182-191. (IBSB2005: Refereed conference).

[J38] N. Nariai, Y. Tamada, S. Imoto and S. Miyano. (2005). Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data. Bioinformatics, 21 Suppl.2, ii206-ii212. (ECCB2005: Refereed conference). (Selected as a full paper with oral presentation out of 209 submitted papers). PDF(354KB)

[J39] S. Imoto*, T. Higuchi*, T. Goto and S. Miyano. (2006). Error tolerant model for incorporating biological knowledge with expression data in estimating gene networks. Statistical Methodology, 3(1), 1-16. (*These authors equally contributed to this work). PDF(1911KB)

[J40] S. Imoto*, Y. Tamada*, H. Araki*, K. Yasuda, C.G. Print, S.D. Charnock-Jones, D. Sanders, C.J. Savoie, K. Tashiro, S. Kuhara and S. Miyano. (2006). Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles. Pacific Symposium on Biocomputing, 11, 559-571. (PSB2006: Refereed conference. Selected as a full paper with oral presentation). (*These authors equally contributed to this work). PDF(487KB)

[J41] R. Nakamichi, S. Imoto and S. Miyano. (2006). Statistical model selection method to analyze combinatorial effects of SNPs and environmental factors for binary disease. International Journal on Artificial Intelligence Tools, 15(5), 711-724.

[J42] R. Yoshida, T. Higuchi, S. Imoto and S. Miyano. (2006). ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles. Bioinformatics, 22, 1538-1539.

[J43] R. Yoshida, K. Numata, S. Imoto, M. Nagasaki, A. Doi, K. Ueno, S. Miyano (2006) A statistical framework for genome-wide discovery of biomarker splice variations with GeneChip Human Exon 1.0 ST Arrays. Genome Informatics, 17(1), 88-99.

[J44] M. Nagasaki, R. Yamaguchi, R. Yoshida, S. Imoto, A. Doi, Y, Tamada, H. Matsuno, S. Miyano, T. Higuchi (2006) Genomic data assimilation for estimating hybrid functional petri net from time-course gene expression data. Genome Informatics, 17(1), 46-61.

[J45] A. Termier, Y. Tamada, S. Imoto, T. Washio and T. Higuchi (2006) From closed tree mining towards closed DAG mining. Proc. International Workshop on Data Mining and Statistical Science, 1-7.

[J46] Y. Tamada, S. Imoto and S. Miyano. (2006). Estimating gene networks from gene expression data utilizing biological information (in Japanese with English abstract). Proc. Inst. Statist. Math., 54(2), 333-356.

[J47] T. Washio, T. Higuchi, S. Imoto, Y. Tamada, K. Sato and H. Motoda. (2006). Graph mining and its application to statistical modeling (in Japanese with English abstract). Proc. Inst. Statist. Math., 54(2), 315-332.

[J48] M. Affara, B. Dunmore, C. Savoie, S. Imoto, Y. Tamada, H. Araki, D.S. Charnock-Jones, S. Miyano and C. Print. (2007) Understanding endothelial cell apoptosis: What can the transcriptome glycome and proteome reveal? Philosophical Transactions of Royal Society, 62(1484), 1469-1487.

[J49] R. Yamaguchi, R. Yoshida, S. Imoto, T. Higuchi and S. Miyano (2007). Finding module-based gene networks with state-space models - Mining high-dimensional and short time-course gene expression data. IEEE Signal Processing Magazine, 24(1), 37-46.

[J50] P.K. Gupta, R. Yoshida, S. Imoto, R. Yamaguchi and S. Miyano (2007). Statistical absolute evaluation of gene ontology terms with gene expression data. Proc. 3rd International Symposium on Bioinformatics Research and Applications, Lecture Note in Bioinformatics, Springer-Verlag. 4463, 146-157. (ISBRA2007: Refereed conference).

[J51] A. Termier, Y. Tamada, K. Numata, S. Imoto, T. Washio, T. Higuchi (2007) DIGDAG, a first algorithm to mine closed frequent embedded sub-DAGs. Proc. 5th International Workshop on Mining and Learning with Graphs, CR-ROM. (MLG2007: Refereed conference).

[J52] R. Yamaguchi, M. Yamamoto, S. Imoto, M. Nagasaki, R. Yoshida, K. Tsuiji, A. Ishige, H. Asou, K. Watanabe, and S. Miyano (2007) Identification of activated transcription factors from microarray gene expression data of Kampo-medicine treated mice. Genome Informatics, 18, 119-129. (IBSB2007: Refereed conference)

[J53] O. Hirose, R. Yoshida, R. Yamaguchi, S. Imoto, T. Higuchi, S. Miyano (2007) Clustering with time course gene expression profiles and the mixture of state space models. Genome Informatics, 18, 258-266. (IBSB2007: Refereed conference)

[J54] K. Numata, S. Imoto, and S. Miyano (2007) A structure learning algorithm for inference of gene networks from microarray gene expression data using Bayesian networks. Proc. IEEE 7th International Symposium on Bioinformatics & Bioengineering, 1280-1284. (IEEE BIBE2007: Refereed conference)

[J55] R. Yoshida, K. Numata, S. Imoto, M. Nagasaki, A. Doi, K. Ueno, and S. Miyano, (2007) Computational discovery of aberrant splice variations with genome-wide exon expression profiles. Proc. IEEE 7th International Symposium on Bioinformatics & Bioengineering, 715-722. (IEEE BIBE2007: Refereed conference)

[J56] S. Imoto (2007) Knowledge discovery of causal relations among genes from microarray gene expression data (in Japanese with English abstract), Journal of Japan Statistical Sciety, 37(1), 55-70.

[J57] T. Shimamura, R. Yamaguchi, S. Imoto and S. Miyano (2007) Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data. Genome Informatics, 19, 142-153. (GIW2007: Refereed conference), (The number of accepted papers is 16 out of 55 submissions).

[J58] T. Ando, S. Konishi and S. Imoto. (2008) Nonlinear regression modeling via regularized radial basis function networks. Journal of Statistical Planning and Inference, 138(11), 3616-3633.

[J59] O. Hirose, R. Yoshida, S. Imoto, R. Yamaguchi, T. Higuchi, Stephen D. Charnock-Jones, C. Print, S. Miyano (2008) Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models, Bioinformatics, 24(7), 932-942.

[J60] O. Hirose, R. Yoshida, R. Yamaguchi, S. Imoto, T. Higuchi and S. Miyano (2008) Analyzing time course gene expression data with biological and technical replicates to estimate gene networks by state space models, Proc. 2nd Asia International Conference on Modelling & Simulation, 940-946. (AMS2008: Refereed conference)

[J61] Y. Hatanaka, M. Nagasaki, R. Yamaguchi, T. Obayashi, K. Numata, A. Fujita, T. Shimamura, T. Tamada, S. Imoto, K. Kinoshita, K. Nakai, S. Miyano (2008) A novel strategy to search conserved transcription factor binding sites among coexpressing genes, Genome Informatics, 20, 212-221.

[J62] K. Kojima, A. Fujita, T. Shimamura, S. Imoto, S. Miyano (2008) Estimation of nonlinear gene regulatory networks via L1 regularized NVAR from time series gene expression data, Genome Informatics, 20, 37-51.

[J63] R. Yamaguchi, S. Imoto, M. Yamauchi, M. Nagasaki, R. Yoshida, T. Shimamura, Y. Hatanaka, K. Ueno, T. Higuchi, N. Gotoh, S. Miyano (2008) Predicting differences in gene regulatory systems by state space models, Genome Informatics, 21, 101-113. (GIW2008: Refereed conference), (The number of accepted papers is 18 out of 55 submissions. This paper is selected as the top three papers in the conference).

[J64] A. Niida, A.D. Smith, S. Imoto, S. Tsutsumi, H. Aburatani, M.Q. Zhang and T. Akiyama (2008) Integrative bioinformatics analysis of transcriptional regulatory programs in breast cancer cells, BMC Bioinformatics, 9:404.

[J65] K. Numata, S. Imoto and S. Miyano (2008) Partial order-based Bayesian network learning algorithm for estimating gene networks, Proc. IEEE Bioinformatics and Biomedicine, 357-360. (BIBM2008: Refereed conference).

[J66] K. Numata, R. Yoshida, M. Nagasaki, A. Saito, S. Imoto and S. Miyano (2008) ExonMiner: Web service for analysis of GeneChip Exon Array data, BMC Bioinformatics, 9:494.

[J67] E. Perrier, S. Imoto and S. Miyano (2008) Finding optimal Bayesian network given a super-structure, Journal of Machine Learning Research, 9, 2251-2286.

[J68] R. Yoshida, M. Nagasaki, R. Yamaguchi, S. Imoto, S. Miyano, T. Higuchi (2008) Bayesian learning of biological pathways on genomic data assimilation, Bioinformatics, 24(22), 2592-2601.

[J69] Y. Watanabe, M. Yamamoto, N. Miura, M. Fukutake, A. Ishige, R. Yamaguchi, M. Nagasaki, S. Imoto, S. Miyano, J. Takeda, K. Watanabe (2008) Orengedokuto and berberine improve indomethacin-induced small intestinal injury via adenosine, Journal of Gastroenterology, 44, 380-389.

[J70] Y. Tamada*, H. Araki*, S. Imoto*, M. Nagasaki, A. Doi, Y. Nakinishi, Y. Tomiyasu, K. Yasuda, B. Dunmore, D. Sanders, S. Humphries, C. Print, D.S. Charnock-Jones, K. Tashiro, S. Kuhara, S. Miyano (2009) Unraveling dynamic activities of autoacine pathways that control drug-response transcriptome networks, Pacific Symposium on Biocomputing, 14, 251-263. (PSB2009: Refereed conference. Selected as a full paper with oral presentation). (*These authors equally contributed to this work).

[J71] A. Niida, A.D. Smith, S. Imoto, S. Tsutsumi, H. Aburatani, M.Q. Zhang and T. Akiyama (2009) Gene set-based module discovery in the breast cancer transcriptome, BMC Bioinformatics, 10:71.

[J72] H. Araki*, Y. Tamada*, S. Imoto*, B. Dunmore, D. Sanders, S. Humphrey, M. Nagasaki, A. Doi, Y. Nakanishi, K. Yasuda, Y. Tomiyasu, K. Tashiro, C. Print, D.S. Charnock-Jones, S. Kuhara, S. Miyano (2009) Analysis of PPAR alpha-dependent and PPAR alpha-independent transcript regulation following fenofibrate treatment of human endothelial cells, Angiogenesis, 12(3), 221-229. (*These authors equally contributed to this work).

[J73] S. Miyano, R. Yamaguchi, Y. Tamada, M. Nagasaki, and S. Imoto (2009) Gene networks viewed through two models, Proceedings of the 1st International Conference on Bioinformatics and Computational Biology (BICoB 2009), Lecture Note in Bioinformatics, 4652, 54-66.

[J74] T. Shimamura, S. Imoto, R. Yamaguchi, A. Fujita, M. Nagasaki, S. Miyano, (2009) Recursive regularization for inferring gene networks from time-course gene expression profiles, BMC Systems Biology, 3, 41.

[J75] A. Niida, S. Imoto, M. Nagasaki, R. Yamaguchi and S. Miyano (2009) A novel meta-analysis approach of cancer transcriptomes reveals prevailing transcriptional networks in cancer cells, Genome Informatics, 22, 121-131.

[J76] K. Kojima, R. Yamaguchi, S. Imoto, M. Yamauchi, M. Nagasaki, R. Yoshida, T. Shimamura, K. Ueno, T. Higuchi, N. Gotoh and S. Miyano (2009) A state space representation of VAR models with sparse learning for dynamic gene networks, Genome Informatics, 22, 56-68.

[J77] N. Yoshikawa, M. Nagasaki, M. Sano, S. Tokudome, K. Ueno, N. Shimizu, S. Imoto, S. Miyano, M. Suematsu, K. Fukuda, C. Morimoto, H. Tanaka (2009) Ligand-based gene expression profiling reveals novel roles of glucocorticoid receptor in cardiac metabolism, American Journal of Physiology, Endocrinology and Metabolism, 296, E1363-E1373.

[J78] Y. Tamada, S. Imoto, H. Araki, M. Nagasaki, C. Print, S. Charnock-Jones, and S. Miyano (2009) Estimating genome-wide gene networks using nonparametric Bayesian network models on massively parallel computers, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.

[J79] R. Yamaguchi, S. Imoto and S. Miyano, (2009) Network-based predictions and simulations by biological state space models: search for drug mode of action, Journal of Computer Science and Technology, in press.

[J80] K. Kojima, E. Perrier, S. Imoto and S. Miyano (2009) Optimal search on clustered structural constraint for learning Bayesian network structure, Journal of Machine Learning Research, in press.

[J81] H. Sato*, H. Nakada*, R. Yamaguchi*, S. Imoto*, S. Miyano and M. Kami (2010) When should we intervene to control the 2009 influenza A(H1N1) pandemic?. Euro Surveillance, 15(1):pii=19455. Available online: http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=19455 (*These authors equally contributed to this work).