Chalkidis, G., Nagasaki, M., Miyano, S. High performance hybrid functional Petri net simulations of biological pathway models on CUDA. IEEE/ACM Transactions on Computational Biology and Bioinformatics. In press.

Do, J.H., Nagasaki, M., Miyano, S. The systems approach to the prespore-specific activation of sigma factor SigF in Bacillus subtilis. Biosystems. 100: 178-184, 2010.

Fujita, A., Kojima, K., Patriota, A.G., Sato, J.R., 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(18):2349-2351, 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, J.R., Demas, M.A.A, Yamaguchi, R., Shimamura, T., Ferreira, C.E., Sogayar, M.C., Miyano, S. Inferring contagion in regulatory networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. In press.

Fujita, A., Sato, J.R., Kojima, K., Gomes, L.R., Sogayar, M.C., Miyano, S. Identification of Granger causality between gene sets. J. Bioinformatics and Computational Biology. 8(4): 679?701, 2010.

Fujita, A., Severino, P., Sato, J.R., 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.

Higashigaki,T., Kojima, K., Yamaguchi, R., Inoue, M., Imoto, S., Miyano, S. Identifying hidden confounders in gene networks by Bayesian networks, Proc. 10th IEEE Bioinformatics and Bioengineering. 168-173, 2010.

International Cancer Genome Consortium, Hudson, T.J. et al. International network of cancer genome projects. Nature. 464(7291):993-998, 2010. Link

Jeong, E., Nagasaki, M., Ueno, K., Miyano, S. Ontology-based instance data validation for high-quality curated biological pathways. BMC Bioinformatics. In press.

Koh, C.H., Nagasaki, M., Saito, A., Wong, L., Miyano, S. DA 1.0: parameter estimation of biological pathways using data assimilation approach. Bioinformatics. 26(14):1794-1796, 2010.

Kojima, K., Imoto, S., Nagasaki, M., Miyano, S. Gene regulatory network clustering for graph layout based on microarray gene expression data, Genome Informatics. 24: 84-95, 2010.

Kojima, K., Nagasaki, M., Miyano, S. An efficient biological pathway layout algorithm combining grid-layout and spring embedder for complicated cellular location information. BMC Bioinformatics. 11:335, 2010.

Kojima, K., Perrier, E., Imoto, S., Miyano, S. Optimal search on clustered structural constraint for learning Bayesian network structure. J. Machine Learning Research.11: 285?310, 2010. Link

Li, C., Nagasaki, M., Saito, A., Miyano, S. Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram. BMC Systems Biology. 4:39, 2010.

Miwa, Y., Li, C., Ge, Q.W., Matsuno, H., Miyano, S., On determining delay time of transitions for Petri net based signaling pathways by introducing stochastic decision rules. In Silico Biol. 10: 0004, 2010. (*Equally contributed) Link

Nagasaki, M., Saito, A., Jeong, E., Li, C., Kojima, K., Ikeda, E., Miyano, S. Cell Illustrator 4.0: A computational platform for systems biology. In Silico Biol. 10: 0002, 2010. Link

Niida, A., Imoto, S., Yamaguchi, R., Nagasaki, M., Miyano, S. Gene set-based module discovery decodes cis-regulatory codes governing diverse gene expression across human multiple tissues. PLoS ONE. 5(6):e10910, 2010.

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. In press.Link

Sato, H, Nakada, H., Yamaguchi, R., Imoto, S., Miyano, S., Kami, M. When should we intervene to control the 2009 influenza A(H1N1) pandemic? Euro Surveill. 7:15(1), pii: 19455, 2010.

Shimamura, T., Imoto, S., Yamaguchi, R., Nagasaki, M., Miyano, S. Inferring dynamic gene networks under varying conditions for transcriptomic network comparison. Bioinformatics. 26(8):1064-1072, 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.

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

Tasaki, S., Nagasaki, M., Kozuka-Hata, H., Semba, K., Gotoh, N., Hattori, S., Inoue, J., Yamamoto, T., Miyano, S., Sugano, S., Oyama, M. Phosphoproteomics-based modeling defines the regulatory mechanism underlying aberrant EGFR signaling. PLoS ONE. In press.

Yamaguchi, R., Imoto, S., Miyano, S. Network-based predictions and simulations by biological state space models: Search for drug mode of action. J. Computer Science and Technology. 25(1): 13-153, 2010.

Yuji, K., Matsumura, T., Miyano, S., Tsuchiya, R., Kami, M. Human papillomavirus vaccine coverage. Lancet. 376(9738):329-330, 2010.

Araki, H.*, Tamada, Y.*, Imoto, S.*, Dunmore, B., Sanders, D., Humphrey, S., Nagasaki, M., Doi, A., Nakanishi, Y., Yasuda, K., Tomiyasu, Y., Tashiro, K., Print, C., Charnock-Jones, D.S., Kuhara, S., Miyano, S. Analysis of PPARalpha-dependent and PPARalpha-independent transcript regulation following fenofibrate treatment of human endothelial cells. Angiogenesis. 12(3): 221-229, 2009. (*Equally contributed).

Do, J.H., Miyano, S., Choi, D.K. Statistical approaches to genome-wide biological networks. Biochip J. 3(3): 190-202, 2009.

Do, J.H., Yamaguchi, R., Miyano, S. Exploring temporal transcription regulation structure of Aspergillus fumigatus in heat shock by state space model. BMC Genomics. 10:306, 2009.

Fujita, A., Sato, J.R., Demas, M.A.A, Yamaguchi, R., Shimamura, T., Ferreira, C.E., Sogayar, M.C., Miyano, S. Inferring contagion in regulatory networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. In press.

Fujita, A., Sato, J.R., Demas, M.A.A, Sogayar, M.C., Ferreira, C.E., Miyano, S. Comparing Pearson, Spearman and Hoeffding's D measure for gene expressionassociation analysis. J. Bioinformatics and Computational Biology. 7(4): 663-684, 2009.

Hashimoto, T.B., Nagasaki, M., Kojima, K., Miyano, S. BFL: a node and edge betweenness based fast layout algorithm for large scale networks. BMC Bioinformatics. 10:19, 2009.

Li, C.*, Nagasaki, M.*#, Ueno, K., Miyano, S. Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension. BMC Systems Biology. 3:42, 2009. doi:10.1186/1752-0509-3-42 (*: These authors equally contributed, #: Corresponding author).

Miyakawa, C., Sugii, M., Matsuno, H., Miyano, S. Computational predictions for functional proteins working after cleaved in apoptotic pathway. Proc. Second International Workshop on Intelligent Informatics in Biology and Medicine, IEEE Computer Society Press, 807-812, 2009.

Miyano, S., Yamaguchi, R., Tamada, Y., Nagasaki, M., Imoto, S. Gene networks viewed through two models. Lecture Notes in Computer Science. 5462: 54-66, 2009. (Proc. First International Conference on Bioinformatics and Computational Biology (BICoB)). doi: 10.1007/978-3-642-00727-9_8.

Nakamura, K., Yoshida, R., Nagasaki, M., Miyano, S., Higuchi, T. Parameter estimation of in silico biological pathways with particle filtering towards a petascale computing. Pacific Symposium on Biocomputing. 14: 227-238, 2009.

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

Tamada, Y., Araki, H., Imoto, S., Nagasaki, M., Doi, A., Nakanishi, Y., Tomiyasu, Y., Yasuda, K., Dunmore, B., Sanders, D., Humphreys, S., Print, C., Charnock-Jones, D.S., Tashiro, K., Kuhara, S., Miyano, S. Unraveling dynamic activities of autocrine pathways that control drug-response transcriptome networks. Pacific Symposium on Biocomputing. 14: 251–263, 2009.

Watanabe-Fukuda, Y., Yamamoto, M., Miura, N., Fukutake, M., Ishige, A., Yamaguchi, R., Nagasaki, M., Saito, A., Imoto, S., Miyano, S., Takeda, J., Watanabe, K. Orengedokuto and berberine improve indomethacin-induced small intestinal injury via adenosine. Journal of Gastroenterology. 44(5):380-389, 2009.

Yamamoto, T., Miyano, S., Nagasaki, M., Bannai, H. Better decomposition heuristics for the maximum-weight connected graph problem using betweenness centrality. Lecture Notes in Artificial Intelligence. In press.

Yashiro, Y., Bannai, H., Minowa, T., Yabiku, T., Miyano, S., Osawa, M., Iwama, A., Nakauchi, H. Transcriptional profiling of hematopoietic stem cells by high-throughput sequencing. I.J. Hematology. 89(1):24-33, 2009.

Yoshikawa, N., Nagasaki, M., Sano, M., Tokudome, S., Ueno, K., Shimizu, N., Imoto, S., Miyano, S., Suematsu, M., Fukuda, K., Morimoto, C., Tanaka, H. Ligand-based gene expression profiling reveals novel roles of glucocorticoid receptor in cardiac metabolism. Am J Physiol Endocrinol Metab. 296(6):E1363-E1373, 2009.

Do, J.H., Miyano, S. The GC and window-averaged DNA curvature profile of secondary metabolite gene cluster in Aspergillus fumigatus genome. Applied Microbiology and Biotechnology. 80(5):841-847, 2008.

Fujita, A., Gomes, L.R., Sato, J.R., Yamaguchi, R., Thomaz, C.E., Sogayar, M.C., Miyano, S. Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates. BMC Systems Biology. 2:106, 2008.

Fujita, A., Sato, J.R., Garay-Malpartida, H.M., Sogayar, M.C., Ferreira, C.E., Miyano, S. Modeling nonlinear gene regulatory networks from time series gene expression data. J. Bioinformatics and Computational Biology. 6(5): 961 – 979, 2008.

Hatanaka, Y., Nagasai, M., Yamaguchi, R., Obayashi, T., Numata, K., Fujita, A., Shimamura, T., Tamada, Y., Imoto, S., Kinoshita, K., Nakai, K., Miyano, S. A novel strategy to search conserved transcription factor binding sites among coexpressing genes in human. Genome Informatics. 20:212-221, 2008.

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

Hirose, O.,Yoshida, R., Yamaguchi, R., Imoto, S., Higuchi, T., Miyano, S. 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, 2008. (AMS2008: Refereed conference)

Jeong, E., Nagasaki, M., Miyano, S. Rule-based reasoning for system dynamics in cell systems. Genome Informatics. 20:25-36, 2008.

Kitakaze, H., Kanda, M., Nakatsuka, H., Ikeda, N., Matsuno, H., Miyano, S. Prediction of fragile points for robustness checking of cell systems. IEICE TRANSACTIONS on Information and Systems D. J91-D(9):2404-2417, 2008.

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

Kojima, K., Nagasaki, M.*, Miyano, S. Fast grid layout algorithm for biological networks with sweep calculation. Bioinformatics. 24(12): 1426-1432, 2008 (*: Corresponding author)

Mito, N., Ikegami, Y., Matsuno, H., Miyano, S., Inouye, S. Simulation analysis for the effect of light-dark cycle on the entrainment in circadian rhythm. Genome Informatics. 21:212-223, 2008.

Nagasaki, M.*, Saito, A., Chen, L., Jeong, E., Miyano, S. Systematic reconstruction of TRANSPATH data into Cell System Markup Language. BMC Systems Biology. 2:53 (23Jun2008), 2008. (*: Corresponding author)

Numata, K., Yoshida, R., Nagasaki, M., Saito, S., Imoto, S., Miyano, S. ExonMiner: Web service for analysis of GeneChip exon array data. BMC Bioinformatics. 9:494, 2008.

Numata, K., Imoto, S., Miyano, S. Partial order-based Bayesian network learning algorithm for estimating gene networks. Proc. IEEE 8th International Symposium on Bioinformatics & Bioengineering, IEEE Computer Society, 357-360, 2008. 　(BIBE2008: Refereed conference; Digital Object Identifier 10.1109/BIBM.2008.85)

Perrier, E., Imoto, S., Miyano, S. Finding optimal Bayesian network given a super-structure. J. Machine Learning Research. 9: 2251-2286, 2008.

Yamaguchi, R., Imoto, S., Yamauchi, M., Nagasaki, M., Yoshida, R., Shimamura, T., Hatanaka, Y., Ueno, K., Higuchi, T., Gotoh, N., Miyano, S. Predicting differences in gene regulatory systems by state space models. Genome Informatics. 21:101-113, 2008.

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

Affara, M., Dunmore, B., Savoie, C.J., Imoto, S., Tamada, Y., Araki, H., Charnock-Jones, D.S., Miyano, S., Print, C. Understanding endothelial cell apoptosis: What can the transcriptome glycome and proteome reveal? Philosophical Transactions of Royal Society. 362(1484):1469-1487, 2007.

Akutsu, T., Bannai, H., Miyano, S., Ott, S. On the complexity of deriving position specific score matrices from positive and negative sequences. Discrete Applied Mathematics.155: 676-685, 2007. (Extended abstract: Proceedings of 13th Annual Symposium on Combinatorial Pattern Matching (CPM 2002). Lecture Notes in Computer Science. 2373:168-177, 2002.)

Fujita, A., Sato, J.R., Garay-Malpartida, H.M., Yamaguchi, R., Miyano, S., Sogayar, M.C., Ferreira, C.E.　Modeling gene expression regulatory networks with the sparse vector autoregressive model. BMC Systems Biology. 1:39, 2007. (doi:10.1186/1752-0509-1-39)

Gupta, P.K., Yoshida, R., Imoto, S., Yamaguchi, R., Miyano, S. Statistical absolute evaluation of gene ontology terms with gene expression data. Lecture Notes in Bioinformatics. 4463:146-157, 2007.

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

Imoto, S., Tamada, Y., Savoie, C.J., Miyano, S., Analysis of gene networks for drug target discovery and validation. Methods in Molecular Biology. 360:33-56, 2007. (Target Discovery and Validation, Volume 1, 33-56, 2007 (a volume of “Methods in Molecular Biology” series), Walker, J. and Sioud, M. (Eds.), Humana Press, USA.).

Imoto, S., Miyano, S. Bayesian network approach to estimate gene networks. A. Mittal, A. Kassim and T. Tan (Eds.), Bayesian Network Technologies: Applications and Graphical Models, Idea Group Publishers, USA. 269-299, 2007. (Refereed book chapter).

Jeong, E.*, Nagasaki, M.*, Miyano, S. Conversion from BioPAX to CSO for system dynamics and visualization of biological pathway. Genome Informatics. 18, 225-236, 2007. (* These authors equally contributed)

Jeong, E.*, Nagasaki, M.*, Saito, A., Miyano, S. Cell System Ontology: Representation for modeling, visualizing, and simulating biological pathways. In Silico Biology 7, 0055, 2007. (* These authors equally contributed)

Kojima, K.*, Nagasaki, M.*, Jeong, E., Kato, M., Miyano, S. An efficient grid layout algorithm for biological networks utilizing various biological attributes. BMC Bioinformatics 2007, 8:76 (6 March 2007). (* These authors equally contributed)

Li, C., Ge, Q.-W., Nakata, M., Matsuno, H., Miyano, S. Modeling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets. J. Biosciences. 32(1):113-125, 2007.

Numata, K., Imoto, S., Miyano, S. 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, 2007. (BIBE2007: Refereed conference; Digital Object Identifier 10.1109/BIBE.2007.4375731)

Saito, A., Nagasaki, M., Oyama, M., Kozuka-Hata, H., Semba, K., Sugano, S., Yamamoto, T., Miyano, S. AYUMS: an algorithm for completely automatic quantitation based on LC-MS/MS proteome data and its application to the analysis of signal transduction. BMC Bioinformatics. 8:15, 2007.

Shimamura, T., Yamaguchi, R., Imoto, S., Miyano, S. Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data. Genome Informatics. 19: 142-153, 2007.

Sugii, M., Okada, R., Matsuno, H., Miyano, S. Performance improvement in protein N-myristoyl classification by BONSAI with insignificant indexing symbol. Genome Informatics. 18: 277-286, 2007.

Yamaguchi, R., Yamamoto, M., Imoto, S., Nagasaki, M., Yoshida, R., Tsujii, K., Ishiga, A., Asou, H., Watanabe, K., Miyano, S. Identification of activated transcription factors from microarray gene expression data of Kampo-medicine treated mice. Genome Informatics. 18: 119-129, 2007.

Yamaguchi, R., Yoshida, R., Imoto, S., Higuchi, T., Miyano, S. 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, 2007.

Yoshida, R., Numata, K., Imoto, S., Nagasaki, M., Doi, A., Ueno, K., Miyano, S. Computational discovery of aberrant splice variations with genome-wide exon expression profiles. Proc. IEEE 7th International Symposium on Bioinformatics & Bioengineering, 715-722, 2007. (IEEE BIBE2007: Refereed conference; Digital Object Identifier 10.1109/BIBE.2007.4375639)

Doi, A., Nagasaki, M., Matsuno, H., Miyano, S. Simulation based validation of the p53 transcriptional activity with hybrid functional Petri net. In Silico Biology. 6(1-2): 1-13, 2006.

Doi, A., Nagasaki, M., Ueno, K., Matsuno, H., Miyano, S. A combined pathway to simulate CDK-dependent phosphorylation and ARF-dependent stabilization for p53 transcriptional activity. Genome Informatics. 17(1): 112-123, 2006.

Imoto, S., Tamada, Y., Araki, H., Yasuda, K., Print, C.G., Charnock-Jones, S.D., Sanders, D., Savoie, C.J., Tashiro, K., Kuhara, S., Miyano, S. Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles. Pacific Symposium on Biocomputing. 11: 559-571, 2006.

Imoto, S., Higuchi, T., Goto, T., Miyano, S. Error tolerant model for incorporating biological knowledge with expression data in estimating gene networks. Statistical Methodology, 3(1):1-16, 2006.

Jeong, E., Miyano, S. A weighted profile based method for protein-RNA interacting residue prediction. Transactions on Computational Systems Biology. Lecture Notes in Computer Science. 3939: 123-139, 2006.

Li, C., Suzuki, S., Ge, Q.-W., Nakata, M., Matsuno, H., Miyano, S. Structural modeling and analysis of signaling pathways based on petri nets. J. Bioinf. Comput. Biol. 4(5):1119-1140, 2006. (On modeling and analyzing signaling pathways with inhibitory interactions based on Petri net. Extended abstract: Proc. The 2005 Internatinal Joint Conference of InCoB, AASBi and KSBI (BIOINFO2005), 348-353, 2005.).

Matsuno, H., Inouye, S.-T., Okitsu, Y., Fujii, Y., Miyano, S. A new regulatory interactions suggested by simulations for circadian genetic control mechanism in mammals. J. Bioinf. Comput. Biol. 4(1): 139-154, 2006. (Extended abstract: Matsuno, H., Inouye, S-T., Okitsu, Y., Fujii, Y., Miyano, S. Proc. The 3rd Asia-Pacific Bioinformatics Conference 2005, Imperial College Press.)

Matsuno, H., Li, C., Miyano, S. Petri net based description for systematic understanding of biological pathways. IEICE Trans. Fundamentals, E89-A (11): 3166-3174, 2006.

Nagasaki, M.*, Yamaguchi, R.*, Yoshida, R., Imoto, S., Doi, A., Tamada, Y., Matsuno, H., Miyano, S., Higuchi, T. Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data. Genome Informatics. 17(1): 46-61, 2006. (* These authors equally contributed)

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

Okada, R., Sugii, M., Matsuno, H., Miyano, S. Machine learning prediction of amino acid patterns in protein N-myristoylation. Lecture Notes in Bioinformatics. 4146: 4-14, 2006. (2006 Workshop on Pattern Recognition In Bioinformatics (PRIB'06))

Saito, A., Nagasaki, M., Doi, A., Ueno, K., Miyano, S. Cell fate simulation model of gustatory neurons with microRNAs double-negative feedback loops by hybrid functional Petri net with extension. Genome Informatics. 17(1): 100-111, 2006.

Takei, Y., Kawakoshi, A., Tsukada, T., Yuge, S., Ogoshi, M., Inoue, K., Hyodo, S., Bannai, H., Miyano, S. Contribution of comparative fish studies to general endocrinology: structure and function of some osmoregulatory hormones. J. Experimental Zoology. Part A, Comparative Experimental Biology. 305(9):787-798, 2006.

Tamada, Y., Imoto, S., Miyano, S. Estimating gene networks from gene expression data utilizing biological information. Proc. Inst. Statist. Math. 54(2): 333-356, 2006.

Tasaki, S., Nagasaki, M., Oyama, M., Hata, H., Ueno, K., Yoshida, R., Higuchi, T., Sugano, S., Miyano, S. Modeling and estimation of dynamic EGFR pathway by data assimilation approach using time series proteomic data. Genome Informatics. 17(2): 226-228, 2006.

Yoshida, R., Higuchi, T., Imoto, S., Miyano, S. ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles. Bioinformatics. 22(12):1538-1539, 2006.

Yoshida, R., Numata, K., Imoto, S., Nagasaki, M., Doi, A., Ueno, K., Miyano, S. 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, 2006.

De Hoon, Michiel J. L., Makita, Y., Nakai, K., Miyano, S. Prediction of transcriptional terminators in Bacillus subtilis and related species. PLoS Computational Biology. 1(3): e25, 2005.

Hirose, O., Nariai, N., Tamada, Y., Bannai, H., Imoto, S., Miyano, S. Estimating gene networks from expression data and binding location data via boolean networks. Lecture Notes in Computer Science. 3482: 349-356, 2005. (Proc. 1st International Conference on Computational Science and Its Applications (Workshop on Data Mining and Bioinformatics)).

Imoto, S., Matsuno, H., Miyano, S. Gene networks: estimation, modeling and simulation. in R. Eils and A. Kriete (Eds.), Computational Systems Biology, Academic Press, 205-228, 2005.

Kato, M., Nagasaki, M., Doi, A., Miyano, S. Automatic drawing of biological networks using cross cost and subcomponent data. Genome Informatics. 16(2): 22-31, 2005.

Kitakaze, H., Matsuno, H., Ikeda, N., Miyano, S. Prediction of debacle points for robustness of biological pathways by using recurrent neural networks. Genome Informatics. 16(1): 192-202, 2005.

Makita, Y., De Hoon, M.J., Ogasawara, N., Miyano, S., Nakai, K. Bayesian joint prediction of associated transcription factors in Bacillus subtilis. Pacific Symposium on Biocomputing. 10: 507-518, 2005.

Nagasaki, M., Doi, A., Matsuno, H., Miyano, S. Petri net modeling of biological pathways. Proc. Algebraic Biology 2005 (Universal Academy Press). 19-31, 2005.

Nagasaki, M., Doi, A., Matsuno, H., Miyano, S. Computational modeling of biological processes with Petri net based architecture. In “Bioinformatics Technologies” (Y.P. Chen, ed). Springer Press. 179-243, 2005.

Nariai, N., Tamada, Y., Imoto, S., Miyano, S. Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data. Bioinformatics. 21: ii206-ii212, 2005.

Ohtsubo, S., Iida, A., Nitta, K., Tanaka, T., Yamada, R., Ohnishi, Y., Maeda, S., Tsunoda, T., Takei, T., Obara, W., Akiyama, F., Ito, K., Honda, K., Uchida, K., Tsuchiya, K., Yumura, W., Ujiie, T., Nagane, Y., Miyano, S., Suzuki, Y., Narita, I., Gejyo, F., Fujioka, T., Nihei, H., Nakamura, Y. Association of a single-nucleotide polymorphism in the immunoglobulin mu-binding protein 2 gene with immunoglobulin A nephropathy. J. Hum. Genet. 50(1): 30-35, 2005.

Ott, S., Hansen, A., Kim, S.-Y., Miyano, S. Superiority of network motifs over optimal networks and an application to the revelation of gene network evolution. Bioinformatics. 21(2): 227-238, 2005.

Tamada, Y., Bannai, H., Imoto, S., Katayama, T., Kanehisa, M., Miyano, S. Utilizing evolutionary information and gene expression data for estimating gene networks with Bayesian network models. J. Bioinformatics and Computational Biology. 3(6): 1295-1313, 2005.

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

Ando, T., Imoto, S., Miyano, S. Bayesian network and radial basis function network regression for nonlinear modeling of genetic network. Proc. Third International Conference on Information. 561-564, 2004.

Ando, T., Imoto, S., Miyano, S. Functional data analysis of the dynamics of gene regulatory networks. Proc. Knowledge Exploration in Life Science Informatics KELSI2004. Lecture Notes in Artificial Intelligence. 3303: 69-83, 2004.

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

Bannai, H., Hyyrö, H., Shinohara, A., Takeda, M., Nakai, K., Miyano, S. An O(N2) algorithm for discovering optimal Boolean pattern pairs. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 1(4): 159-170, 2004. (Extended abstract: Bannai, H., Hyyrö, H., Shinohara, A., Takeda, M., Nakai, K., Miyano, S. Finding optimal pairs of patterns. Proc. 4th International Workshop on Algorithms in Bioinformatics (WABI 2004). Lecture Notes in Bioinformatics. 3240:450-462, 2004.)

Bannai, H., Inenaga, S., Shinohara, A., Takeda, M., Miyano, S. Efficiently finding regulatory elements using correlation with gene expression. J. Bioinformatics and Computational Biology. 2(2):273-288, 2004.

De Hoon, M.J.L., Imoto, S., Kobayashi, K., Ogasawara, N., Miyano, S. Predicting the operon structure of Bacillus subtilis using operon length, intergene distance, and gene expression information. Pacific Symposium on Biocomputing. 9:276-287, 2004.

De Hoon, M.J.L., Imoto, S., Nolan, J., Miyano, S. Open source clustering software. Bioinformatics. 20(9):1453-1454, 2004.

De Hoon, M.J.L., Makita, Y., Imoto, S., Kobayashi, K., Ogasawara, N., Nakai, K., Miyano, S. Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data. Bioinformatics, 20(Suppl.1):i101-i108, 2004.

Doi, A., Fujita, S., Matsuno, H., Nagasaki, M., Miyano, S. Constructing biological pathway models with hybrid functional Petri nets. In Silico Biology. 4(3):271-291, 2004.

Fujita, S., Matsui, M., Matsuno, H., Miyano, S. Modeling and simulation of fission yeast cell cycle on hybrid functional Petri net. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. E87-A(11):2919-2928, 2004.

Imoto, S., Higuchi, T., Kim, S., Jeong, E., Miyano, S. Residual bootstrapping and median filtering for robust estimation of gene networks from microarray data. Proc. 2nd Computational Methods in Systems Biology. Lecture Notes in Bioinformatics. 3082:149-160, 2004.

Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S., Miyano, S. Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks. J. Bioinformatics and Computational Biology. 2(1):77-98, 2004.

Inenaga, S., Bannai, H., Hyyrö, H., Shinohara, A., Takeda, M., Nakai, K., Miyano, S. Finding optimal pairs of cooperative and competing patterns with bounded distance. Proc. 7th International Conference on Discovery Science (DS 2004). Lecture Notes in Artificial Intelligence. 3245:32-46, 2004.

Jeong, E., Chung, I., Miyano, S. A neural network method for identification of RNA-interacting residues in protein. Genome Informatics. 15(1):105-116, 2004.

Kim, S., Imoto, S., Miyano, S. Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data. Biosystems. 75(1-3): 57-65, 2004. (Extended abstract: Proceedings of First Computational Methods in Systems Biology. Lecture Notes in Computer Science. 2602:104-113, 2003.)

Matsui, M., Fujita, S., Suzuki, S., Matsuno, H., Miyano, S. Simulated cell division processes of the Xenopus cell cycle pathway by Genomic Object Net. J. Integrative Bioinformatics. 3: 95-104, 2004. (http://journal.imbio.de/index.php?paper_id=3, 2004.)

Miyano, S. Computational systems biology. Proc. Third International Conference on Information (Li, L. and Yen, K.K., Eds.). 9-14, 2004.

Nagasaki, M., Doi, A., Matsuno, H., Miyano, S. Integrating biopathway databases for large-scale modeling and simulation. Proc. Second Asia-Pacific Bioinformatics Conference (APBC2004) (Y.P. Chen, Ed.). Conferences in Research and Practice in Information Technology. 29: 43-52, 2004.

Nagasaki, M., Doi, A., Matsuno, H., Miyano, S. A versatile Petri net based architecture for modeling and simulation of complex biological processes. Genome Informatics. 15(1):180-197, 2004.

Nakamichi, R., Imoto, S., Miyano, S. Case-control study of binary trait considering interactions between SNPs and environmental effects using logistic regression. Proc. 4th IEEE Bioinformatics and Bioengineering. IEEE Press. 73-78, 2004.

Nakano, M., Noda, R., Kitakaze, H., Matsuno, H., Miyano, S. XML pathway file conversion between Genomic Object Net and SBML. Proc. The Third International Conference on Information. 585-588, 2004.

Nariai, N., Kim, S., Imoto, S., Miyano, S. Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks. Pacific Symposium on Biocomputing. 9:336-347, 2004.

Ott, S., Imoto, S., Miyano, S. Finding optimal models for small gene networks. Pacific Symposium on Biocomputing. 9:557-567, 2004.

Takei, Y., Inoue, K., Ogoshi, M., Kawahara, T., Bannai, H., Miyano, S. Identification of novel adrenomedullin in mammals: a potent cardiovascular and renal regulator. FEBS Letters, 556:53-58, 2004.

Akutsu, T., Kuhara, S., Maruyama, O., Miyano, S. Identification of genetic networks by strategic gene disruptions and gene overexpressions under a boolean model. Theoretical Computer Science. 298(1):235-251, 2003. (Extended abstract: Proceedings of 9th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'98), 695-702, 1998.)

Akutsu, T., Miyano, S., Kuhara, S. A simple greedy algorithm for finding functional relations: efficient implementation and average case analysis. Theoretical Computer Science. 292(2):481-495, 2003. (Extended abstract: Proceedings of Third International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 1967:86-98, 2000.)

De Hoon, M., Imoto, S., Kobayashi, K., Ogasawara, N., Miyano, S. Inferring gene regulatory networks from time-ordered gene expression data of Bacillus subtilis using differential equations. Pacific Symposium on Biocomputing. 8:17-28, 2003.

Doi, A., Nagasaki, M., Matsuno, H., Miyano, S. Genomic Object Net: II. Modelling biopathways by hybrid functional Petri net with extension. Applied Bioinformatics. 2(3):185-188, 2003.

Imoto, S., Kim, S., Goto, T., Aburatani, S., Tashiro, K., Kuhara, S., Miyano, S. Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. Journal of Bioinformatics and Computational Biology. 1(2):231-252, 2003. (Extended abstract: Proceedings of IEEE Computer Society Bioinformatics Conference. 219-227, 2002.) (Extended abstract: Proceedings of Second Computational Systems Bioinformatics, 104-113, 2003.)

Imoto, S., Savoie, C.J., Aburatani, S., Kim, S., Tashiro, K., Kuhara, S., Miyano, S. Use of gene networks for identifying and validating drug targets. Journal of Bioinformatics and Computational Biology. 1(3):459-474, 2003.

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

Matsuno, H., Murakami, R., Yamane, R., Yamasaki, N., Fujita, S., Yoshimori, H., Miyano, S. Boundary formation by notch signaling in Drosophila multicellular systems: experimental observations and gene network modeling by Genomic Object Net. Pacific Symposium on Biocomputing. 8:152-163, 2003.

Matsuno, H., Tanaka, Y., Aoshima, H., Doi, A., Matsui, M., Miyano, S. Biopathways representation and simulation on hybrid functional Petri net. In Silico Biology. 3(3): 389-404, 2003.

Matsuno, H., Fujita, S., Doi, A., Nagasaki, M., Miyano, S. Towards biopathway modeling and simulation. Proceedings of 24th International Conference on Applications and Theory of Petri Nets (ICATPN 2003). Lecture Notes in Computer Science. 2679:3-22, 2003.

Miyano, S. Inference, modeling and simulation of gene networks. Proceedings of International Workshop on Computational Methods in Systems Biology. Lecture Notes in Computer Science. 2602:207-211, 2003.

Nagasaki, M. Doi, A., Matsuno, H., Miyano, S. Genomic Object Net: I. a platform for modeling and simulating biopathways. Applied Bioinformatics. 2(3):181-184, 2003.

Nagasaki, M., Doi, A., Matsuno, H., Miyano, S. Recreating biopathway databases towards simulation. Proceedings of International Workshop on Computational Methods in Systems Biology. Lecture Notes in Computer Science. 2602:191-192, 2003.

Obara, W., Iida, A., Suzuki, Y., Tanaka, T., Akiyama, F., Maeda, S., Ohnishi, Y., Yamada, R., Tsunoda, T., Takei, T., Ito, K., Honda, K., Uchida, K., Tsuchiya, K., Yumura, W., Ujiie, T., Nagane, Y., Nitta, K., Miyano, S., Narita, I., Gejyo, F., Nihei, H., Fujioka, T., Nakamura, Y. Association of single-nucleotide polymorphisms in the polymeric immunoglobulin receptor gene with immunoglobulin A nephropathy (IgAN) in Japanese patients. J Hum Genet. 48(6):293-299, 2003.

Ott, S., Tamada, Y., Bannai, H., Nakai, K., Miyano, S. Intrasplicing - analysis of long intron sequences. Pacific Symposium on Biocomputing. 8:339-350, 2003.

Ott, S., Miyano, S. Finding optimal gene networks using biological constraints. Genome Informatics. 14:124-133, 2003.

Savoie, C.J., Aburatani, S., Watanabe, S., Eguchi, Y., Muta, S., Imoto, S., Miyano, S., Kuhara, S., Tashiro, K. Use of gene networks from full genome microarray libraries to identify functionally relevant drug-affected genes and gene regulation cascades. DNA Research. 10(1):19-25, 2003.

Tamada, Y., Kim, S., Bannai, H., Imoto, S., Tashiro, K., Kuhara, S., Miyano, S. Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection. Bioinformatics. 19(Suppl.2):ii227-ii236, 2003.

Takei, Y., Inoue, K., Ogoshi, M., Kawahara, T., Bannai, H., Miyano, S. Identification of novel adrenomedullin in mammals: a potent cardiovascular and renal regulator. FEBS Letters, 556(1-3):53-58, 2003.

Akiyama, F., Tanaka, T., Yamada, R., Ohnishi, Y., Tsunoda, T., Maeda, S., Takei, T., Obara, W., Ito, K., Honda, K., Uchida, K., Tsuchiya, K., Nitta, K., Yumura, W., Nihei, H., Ujiie, T., Nagane, Y., Miyano, S., Suzuki, Y., Fujioka, T., Narita, I., Gejyo, F., Nakamura, Y. Single-nucleotide polymorphisms in the class II region of the major histocompatibility complex in Japanese patients with immunoglobulin A nephropathy. J. Hum. Genet. 47(10):532-538, 2002.

Akutsu, T., Miyano, S. Selecting informative genes for cancer classification using gene expression data. Computational and Statistical Approaches to Genomics (W. Zhang and I. Shmulevich eds.). Kluwer Academic Pub. 79-92, 2002.

Bannai, H. Inenaga, S., Shinohara, A., Takeda, M., Miyano, S. A string pattern regression algorithm and its application to pattern discovery in long introns. Genome Informatics. 13:3-11, 2002.

Bannai, H., Tamada, Y., Maruyama, O., Nakai, K., Miyano, S. Extensive feature detection of N-terminal protein sorting signals. Bioinformatics. 18(2):298-305, 2002.

De Hoon, M., Imoto, S., Miyano, S. Inferring gene regulatory networks from time-ordered gene expression data using differential equations. Proceedings of Fifth International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 2534:267-274, 2002.

De Hoon, M.J.L., Imoto, S., Miyano, S. Statistical analysis of a small set of time-ordered gene expression data using linear splines. Bioinformatics. 18(11):1477-1485, 2002.

Imoto, S., Goto, T., Miyano, S. Estimation of genetic networks and functional structures between genes by using Bayesian network and nonparametric regression. Pacific Symposium on Biocomputing. 7:175-186, 2002.

Maruyama, O., Bannai, H., Tamada, Y., Kuhara, S., Miyano, S. Fast algorithm for extracting multiple unordered short motifs using bit operations. Information Sciences. 146(1-4):115-126, 2002.

Maruyama, O., Shoudai, T., Miyano, S. Toward drawing an atlas of hypothesis classes: approximating a hypothesis via another hypothesis model. Proc. 5th International Conference on Discovery Science (DS2002). Lecture Notes in Computer Science. 2534:220-232, 2002.

Takei, T., Iida, A., Nitta, K., Tanaka, T., Ohnishi, Y., Yamada, R., Maeda, S., Tsunoda, T., Takeoka, S., Ito, K., Honda, K., Uchida, K., Tsuchiya, K., Suzuki, Y., Fujioka, T., Ujiie, T., Nagane, Y., Miyano, S., Narita, I., Gejyo, F., Nihei, H., Nakamura, Y. Association between single-nucleotide polymorphisms in selectin genes and immunoglobulin A nephropathy. Am. J. Hum. Genet. 70(3):781-786, 2002.

Tamada, Y., Bannai, H., Maruyama, O., Miyano, S. Foundations of designing computational knowledge discovery processes. Progress in Discovery Science. Lecture Notes in Computer Science. 2281:459-470, 2002.

Bannai, H., Tamada, Y., Maruyama, O., Miyano, S. VML: a view modeling language for computational knowledge discovery. Proceedings of Fourth International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 2226:30-44, 2001.

Bannai, H., Tamada, Y., Maruyama, O., Miyano, S. HypothesisCreator: Concepts for accelerating the computational knowledge discovery process. Electronic Transactions on Artificial Intelligence. 5:73-83, 2001. (Electronic version: Linkoping Electronic Articles in Computer and Information Science. Issue: Vol. 6 (2001), No. 019. URL: http://www.ep.liu.se/ea/cis/2001/019/.)

Bannai, H., Tamada, Y., Maruyama, O., Nakai, K., Miyano, S. Views: fundamental building blocks in the process of knowledge discovery. Proceedings of the 14th International FLAIRS Conference. AAAI Press. 233-238, 2001.

Maruyama, O., Shoudai, T., Furuichi, E., Kuhara, S., Miyano, S. Learning conformation rules. Proceedings of Fourth International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 2226:243-257, 2001.

Matsuno, H., Doi, A., Hirata, Y., Miyano, S. XML Documentation of biopathways and their simulations in Genomic Object Net. Genome Informatics. 12:54-62, 2001.

Onami, S., Hamahashi, S., Nagasaki, M., Miyano, S., Kitano, H. Automatic acquisition of cell lineage through 4D micorscopy and analysis of early C. elegans embryogenesis. Foundations of Systems Biology, Kitano, H. (ed.), MIT Press. 39-55, 2001.

Sim, K.L., Uchida, T., Miyano, S. ProDDO: a database of disordered proteins form the Protein Data Bank (PDB). Bioinformatics 17(4):379-380, 2001.

Akutsu, T., Miyano, S., Kuhara, S. Inferring qualitative relations in genetic networks and metabolic pathways. Bioinformatics. 16(8):727-734, 2000.

Akutsu, T., Miyano, S., Kuhara, S. Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function. Journal of Computational Biology. 7(3-4):331-343, 2000. (Extended abstract: Proceedings of Fourth Annual International Conference on Computational Molecular Biology. 8-24, 2000.)

Akutsu, T., Miyano, S., Kuhara, S. Algorithms for inferring qualitative models of biological networks. Pacific Symposium on Biocomputing. 5:293-304, 2000.

Maruyama, O., Miyano, S. Design sspects of discovery systems. IEICE Transactions on Information and Systems. E83-D(1):61-70, 2000.

Matsuno, H., Doi, A., Nagasaki, M., Miyano, S. Hybrid Petri net representation of gene regulatory network. Pacific Symposium on Biocomputing. 5:341-352, 2000.

Miyano, S., Shinohara, A., Shinohara, T. Polynomial-time learning of elementary formal systems. New Generation Computing. 18(3):217-242, 2000.

Tanaka, M., Nakazono, S., Matsuno, H., Tsujimoto, H., Kitamura, Y., Miyano, S. Intelligent system for topic survery in MEDLINE by keyword recommendation and learning text characteristics. Genome Informatics. 11:73-82, 2000.

Akutsu, T., Miyano, S. On the approximation of protein threading. Theoretical Computer Science. 210:261-275, 1999. (Extended abstract: Proceedings of the First Annual International Conference on Research in Computational Molecular Biology. 3-8, 1997.)

Akutsu, T., Miyano, S., Kuhara, S. Identification of genetic networks from a small number of gene expression patterns under the boolean network model. Pacific Symposium on Biocomputing. 4:17-28, 1999.

Bannai, H., Miyano, S. A definition of discovery in terms of generalized descriptional complexity. Proceedings of Second International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 1721:316-318, 1999.

Maruyama, O., Uchida, T., Sim, K.L., Miyano, S. Designing views in HypothesisCreator: System for assisting in discovery. Proceedings of Second International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 1721:115-127, 1999.

Moriyama, T., Shinohara, A., Takeda, M., Maruyama, O., Goto, T., Miyano, S., Kuhara, S. A system to find genetic networks using weighted network model. Genome Informatics. 10:186-195, 1999.

Nagasaki, M., Onami, S., Miyano, S., Kitano, H. Bio-calculus: its concept and molecular interaction. Genome Informatics. 10:133-143, 1999.

Yasuda, T., Bannai, H., Onami, S., Miyano, S., Kitano, H. Towards automatic construction of cell-linearge of C. elegans from Normarski DIC microscope images. Genome Informatics. 10:144-154, 1999.

Akutsu, T., Maruyama, O., Miyano, S., Kuhara, S. A system for identifying genetic networks from gene expression patterns produced by gene disruptions and overexpressions. Genome Informatics. 9:151-160, 1998.

Maruyama, O., Uchida, T., Shoudai, T., Miyano, S. Toward Genomic Hypothesis Creator: View Designer for Discovery. Proceedings of First International Conference on Discovery Science. Lecture Notes in Artificial Intelligence. 1532:105-116, 1998.

Noda, K., Shinohara, A., Takeda, M., Matsumoto, S., Miyano, S., Kuhara, S. Finding genetic network from experiments by weighted network model. Genome Informatics. 9:141-150, 1998.

Usuzaka, S., Sim, K.L., Tanaka, M., Matsuno, H., Miyano, S. A machine learning approach to reducing the work of experts in article selection from database: a case study for regulatory relations of S. cerevisiae genes in MEDLINE. Genome Informatics. 9:91-101, 1998.

Yamaguchi, A., Nakano, K., Miyano, S. An approximation algorithm for the minimum common supertree problem. Nordic J. Computing. 4(2):303-316, 1997.

Miyano, S. Genome Informatics: New Frontiers of Computer Science and Biosciences. Cooperative Databases and Applications (Advances Database Research and Development Series Vol. 7). Edited by Kambayashi, Y. and Yokota, K. (World Scientific). 12-21, 1997.

Furukawa, N., Matsumoto, S., Shinohara, A., Shoudai, T., Miyano, S. HAKKE: A multi-strategy prediction system for sequences. Genome Informatics. 7:98-107, 1996.

Maruyama, O., Miyano, S. Taking a walk on a graph. Mathematica Japonica. 43(3):595-606, 1996.

Maruyama, O., Miyano, S. Inferring a tree from walks. Theoretical Computer Science. 161(1-2):289-300, 1996.

Tateishi, E., Miyano, S. A greedy strategy for finding motifs from yes-no examples. Pacific Symposium on Biocomputing. 1:599-613, 1996.

Tateishi, E., Maruyama, O., Miyano, S. Extracting best consensus motifs from positive and negative examples. Proceedings of the 13th Annual Symposium on Theoretical Aspects of Computer Science. Lecture Notes in Computer Science. 1046:219-230, 1996.

Miyano, S. Learning theory towards genome informatics. IEICE Transactions on Information and Systems. E78-D(5):560-567, 1995. (Invited paper: Miyano, S. Learning theory towards genome informatics. Proc. 4th International Workshop on Algorithmic Learning Theory, Lecture Notes in Computer Science. 744: 19-36, 1993.)

Shimozono, S., Miyano, S. Complexity of finding alphabet indexing. IEICE Transactions on Information and Systems. E78-D(1):13-18, 1995.

Shoudai, T., Miyano, S. Using maximal independent sets to solve problems in parallel. Theoretical Computer Science. 148(1):57-65, 1995.

Uchida, T., Shoudai, T., Miyano, S. Parallel algorithms for refutation tree problem on elementary formal graph systems. IEICE Transactions on Information and Systems. E78-D(2):99-112, 1995.

Shoudai, T., Lappe, M., Miyano, S., Shinohara, A., Okazaki, T., Arikawa, S., Uchida, T., Shimozono, S., Shinohara, T., Kuhara, S. BONSAI Garden: parallel knowledge discovery system for amino acid sequences. Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology. AAAI Press. 359-366, 1995.

Miyano, S., Shimozono, S., Maruyama, O. Some algorithmic problems arising from genome informatics. Advances in Computing Techniques - Algorithms, Databases and Prallel Processing. World Scientific, 45-59, 1995.

Uchida, T., Shoudai, T., Miyano, S. Polynomial time algorithm solving the refutation tree problem for formal graph systems. Bulletin of Informatics and Cybernetics. 26(1-2):55-74, 1994.

Arikawa, S., Kuhara, S., Miyano, S., Mukouchi, Y., Shinohara, A., Shinohara, T. A machine discovery from amino acid sequences by decision trees over regular patterns. New Generation Computing. 11(3):361-375, 1993.

Arikawa, S., Shinohara, T., Miyano, S., Shinohara, A. More about learning elementary formal systems. Proceedings of Second International Workshop on Nonmonotonic and Inductive Logic. Lecture Notes in Computer Science. 659:107-117, 1993.

Furuya, S., Miyano, S. NP-hard aspects in analogical reasoning. Bulletin of Informatics and Cybernetics. 25(3-4):155-159, 1993.

Shimozono, S., Shinohara, A., Shinohara, T., Miyano, S., Kuhara, S., Arikawa, S. Finding alphabet indexing for decision trees over regular patterns: an approach to bioinformatical knowledge acquisition. Proceedings of the Twenty-Sixth Hawaii International Conference on System Sciences, Vol. I. IEEE Computer Society Press. 763-772, 1993.

Shimozono, S., Shinohara, A., Shinohara, T., Miyano, S., Kuhara, S., Arikawa, S. Knowledge acquisition from amino acid sequences by machine learning system BONSAI. Transactions on Information Processing Society of Japan. 35(10):2009-2018, 1993.

Shinohara, A., Shimozono, S., Uchida, T., Miyano, S. Kuhara, S., Arikawa, S. Running learning systems in parallel for machine discovery from sequences. Genome Informatics. 4:74-83, 1993.

Shoudai, T., Miyano, S. A parallel algorithm for the maximal co-hitting set problem. IEICE Transactions on Information and Systems. E76-D(2):296-298, 1993.

Uchida, T., Miyano, S. O(log*n) time parallel algorithm for computing bounded degree maximal subgraphs. Journal of Information Processing. 16(1):16-20, 1993.

Arikawa, S., Kuhara, S., Miyano, S., Shinohara, A., Shinohara, T. A learning algorithm for elementary formal systems and its experiments on identification of transmembrane domains. Proceedings of the Twenty-Fifth Hawaii International Conference on System Science, Vol. I. IEEE Computer Society Press. 675-684, 1992.

Arikawa, S., Miyano, S., Shinohara, A., Shimozono, S., Shinohara, T., Kuhara, S. Knowledge acquisition from amino acid sequences by learning algorithms. Proceedings of the Second Japanese Knowledge Acquisition for Knowledge-Based Systems Workshop. 109-128, 1992.

Arikawa, S., Miyano, S., Shinohara, A., Shinohara, T., Yamamoto, A. Algorithmic learning theory with elementary formal systems. IEICE Transactions on Information and Systems. E75-D(4):405-414, 1992.

Furuya, S., Miyano, S. NP-complete problems on label updating calculation in ATMS. Bulletin of Informatics and Cybernetics. 25(1-2):1-5, 1992.

Furuya, S., Miyano, S. Analogy is NP-hard. Proceedings of the Second Workshop on Algorithmic Learning Theory. 207-212, 1991.

Miyano, S. Δ^p₂complete lexicographcially first maximal subgraph problems. Theoretical Computer Science. 88(1):33-57, 1991.

Miyano, S., Shinohara, A., Shinohara, T. Which classes of elementary formal systems are polynomial-time learnable? Proceedings of the Second Workshop on Algorithmic Learning Theory. 139-150, 1991.

Shinohara, A., Miyano, S. Teachability in computational learning. New Generation Computing. 8(4):337-347, 1991.

Miyano, S. Systematized approaches to the complexity of subgraph problems. Journal of Information Processing. 13(4):442-448, 1990.

Arikawa, S., Haraguchi, M., Inoue, H., Kawasaki, Y., Miyahara, T., Miyano, S., Oshima, K., Sakai, H., Shinohara, T., Shiraishi, S., Takeda, M., Takeya, S., Yamamoto, A., Yuasa, H. The text database management system SIGMA: an improvement of the main engine. Proceedings of Berliner Informatik-Tage. 72-81, 1989.

Miyano, S. The lexicographically first maximal subgraph problems - P-completeness and NC algorithms. Mathematical Systems Theory. 22(1):47-73, 1989.

Miyano, S. A parallelizable lexicographically first edge-induced subgraph problem. Information Processing Letters. 27(2):75-78, 1988.

Miyano, S. Indexing alternating finite automata and binary tree like circuits. Bulletin of Informatics and Cybernetics. 23(1-2):79-88, 1988.

Miyano, S. Parallel complexity and P-complete problems. Proceedings of International Conference on Fifth Generation Computer Systems 1988. 532-541, 1988.

Hayashi, T., Miyano, S. Finite tree automata on infinite trees. Bulletin of Informatics and Cybernetics. 21(3-4):71-82, 1985.

Miyano, S. Remarks on two-way automata with weak-counters. Information Processing Letters. 18(2):105-107, 1984.

Miyano, S., Hayashi, T. Alternating finite automata on ω-words. Theoretical Computer Science. 32(3):321-330, 1984.

Miyano, S. Remarks on multihead pushdown automata and multihead stack automata. Journal of Computer and System Sciences. 27(1):116-124, 1983.

Miyano, S. Two-way deterministic multi-weak-counter machines. Theoretical Computer Science. 21(1):27-32, 1982.

Miyano, S. A hierarchy theorem for multihead stack-counter automata. Acta Informatica. 17(1):63-67, 1982.

Miyano, S., Haraguchi, M. Recovery of incomplete tables under functional dependencies. Bulletin of Informatics and Cybernetics. 20(1-2):25-41, 1982.

Miyano, S. One-way weak-stack-counter automata. Journal of Computer and System Sciences. 20(1):59-76, 1980.

Miyano, S. On a lower bound of Shepherdson function. Memoirs of the Faculty of Science, Kyushu University, Ser. A. 33(2):257-267, 1979.

Hirokawa, S., Miyano, S. A note on the regularity of fuzzy languages. Memoirs of the Faculty of Science, Kyushu University, Ser. A. 32(1):61-66, 1978.

Miyano, S. On an automaton which recognizes a family of automata. Memoirs of the Faculty of Science, Kyushu University, Ser. A. 32(1):37-51, 1978.

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

Fujita, A., Sato, J.R., Demasi, M.A.A., Miyano, S., Sogayar, M.C., Ferreira, C.E. An introduction to time-varying connectivity estimation for gene regulatory networks. Frank Emmert-Streib; Matthias Dehmer. (Org.). Medical Biostatistics for complex diseases. Weinheim, Germany: Wiley VCH Verlag, p.205-230, 2010.

Mitou, N., Matsuno, H., Miyano, S., Inouye, S. Essential role of Ror gene in the interaction of feedback loops in mammalian circadian clocks. In press.

Saito, A., Nagasaki, M., Miyano, S. Hybrid functional Petri net with extension for dynamic pathway modeling. In press.

Imoto, S., Tamada, Y., Savoie, C.J., Miyano, S., Analysis of gene networks for drug target discovery and validation. Methods in Molecular Biology. 360:33-56, 2007. (Target Discovery and Validation, Volume 1, 33-56, 2007 (a volume of “Methods in Molecular Biology” series), Walker, J. and Sioud, M. (Eds.), Humana Press, USA.).

Imoto, S., Miyano, S. Bayesian network approach to estimate gene networks. A. Mittal, A. Kassim and T. Tan (Eds.), Bayesian Network Technologies: Applications and Graphical Models, Idea Group Publishers, USA. 269-299, 2007. (Refereed book chapter).

Nagasaki, M., Doi, A., Matsuno, H., Miyano, S. Computational modeling of biological processes with Petri net based architecture. In “Bioinformatics Technologies” (Y.P. Chen, ed). Springer Press. 179-243, 2005.

Akutsu, T., Miyano, S. Selecting informative genes for cancer classification using gene expression data. Computational and Statistical Approaches to Genomics (W. Zhang and I. Shmulevich, Eds.). Kluwer Academic Pub. 79-92, 2002.

Akutsu, T., Miyano, S. Selecting informative genes for cancer classification using gene expression data. Computational and Statistical Approaches to Genomics (W. Zhang and I. Shmulevich eds.). Kluwer Academic Pub. 79-92, 2002.

Miyano, S. Genome Informatics: New Frontiers of Computer Science and Biosciences. Cooperative Databases and Applications (Advances Database Research and Development Series Vol. 7). edited by Kambayashi, Y. and Yokota, K. (World Scientific), 12-21, 1997.

Nagasaki, M., Saito, A., Doi, A., Matsuno, H., Miyano, S. “Foundations of Systems Biology - Using Cell Illustrator and Pathway Databases”. Springer, 2009. Springer

Kurata, H., Miyano, S. （Japanese Translation). Uri Alon. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/CRC, 2007）. Kyoritsu Shuppan Co. Ltd., 2008.

Doi, A., Nagasaki, M., Saito, A., Matsuno, H., Miyano, S. “Yes, We Can Understand Systems Biolog! - Let's use Cell Illustrator” (in Japanese). Kyoritsu Shuppan, Co. Ltd., 2007.

Miyano, S. “Parallel Algorithms - Theory and Design” (in Japanese). Kindai kagaku sha Co. Ltd., 1993.

Arikawa, S., Miyano, S. “Automata and Computability” (in Japanese). Baifukan Co. Ltd., 1986.

Ferreira, C.E., Miyano, S., Stadler, P.F. (Eds.) Advances in Bioinformatics and Computational Biology, Springer, 2010.

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