Supercomputer

Results Achieved by Using the Supercomputer (Published Papers)

If there are any additional papers that have not been included in the above list, please contact us at the e-mail address below. Thank you.
    

Published Papers List in 2014
Published Papers List in 2013
Published Papers List in 2012
Published Papers List in 2011
Published Papers List in 2010
Published Papers List in 2009
Published Papers List in 2008
Published Papers List before 2008

Published Papers List before 2008

AuthorTitleJournal/Book
Kushida T, Takagi T, Fukuda KI Event ontology: a pathway-centric ontology for biological processes Pac Symp Biocomput. 2006:152-63. pubmed
Fukuda K, Yamamoto S, Sakai N, Nakamura H, Nakanishi Y, Takagi T "Graphical syntax and query for pathway database." The 10th World Multi-Conference on Systemics, Cybernetics and Informatics proceedings (WMSCI2006), Vol.IV, 7-10, ISBN:980-6560-65-5, 2006
福田 賢一郎 BioPAX: パスウェイデータフォーマットの標準化とオントロジー 生物物理 Vol.47 No.3, 179-84, 2007
福田 賢一郎, 五斗 進 バイオデータベースの今:4. バイオ知識の形成と表現 情報処理学会誌 Vol.47 No.3, 233-240, 2006
福田 賢一郎 生命科学におけるオントロジーとその利用 人工知能学会誌 Vol.22 No.1, 70-76, 2007
Affara M, Dunmore B, Savoie C, Imoto S, Tamada Y, Araki H, Charnock-Jones DS, Miyano S, Print C Understanding endothelial cell apoptosis: what can the transcriptome, glycome and proteome reveal? Philos Trans R Soc Lond B Biol Sci. 2007 Aug 29;362(1484):1469-87. pubmed
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. 2002;47(10):532-8. pubmed
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. Proceedings of 13th Annual Symposium on Combinatorial Pattern Matching (CPM 2002). Lecture Notes in Computer Science, 2373, 168-177, 2002
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. Proceedings of 9th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'98), 695-702, 1998
Akutsu T, Kuhara S, Maruyama O, Miyano S A System for Identifying Genetic Networks from Gene Expression Patterns Produced by Gene Disruptions and Overexpressions Genome Inform Ser Workshop Genome Inform. 1998;9:151-160. pubmed
Akutsu T, Miyano S On the approximation of protein threading Theoretical Computer Science, 210, 261-275, 1999. Proceedings of the First Annual International Conference on Research in Computational Molecular Biology. 3-8, 1997
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, Kuhara S A simple greedy algorithm for finding functional relations: efficient implementation and average case analysis Theoretical Computer Science, 292(2), 481-495, 2003. Proceedings of Third International Conference on Discovery Science. Lecture Notes in Artificial Intelligence, 1967, 86-98, 2000
Akutsu T, Miyano S, Kuhara S Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function J Comput Biol. 2000;7(3-4):331-43. pubmed
Akutsu T, Miyano S, Kuhara S Algorithms for inferring qualitative models of biological networks Pac Symp Biocomput. 2000:293-304. pubmed
Akutsu T, Miyano S, Kuhara S Identification of genetic networks from a small number of gene expression patterns under the Boolean network model Pac Symp Biocomput. 1999:17-28. pubmed
Akutsu T, Miyano S, Kuhara S Inferring qualitative relations in genetic networks and metabolic pathways Bioinformatics. 2000 Aug;16(8):727-34. pubmed
Ando T, Imoto S, Konishi S Adaptive learning machines for nonlinear classification and Bayesian information criterion Bulletin of Informatics and Cybernetics, 36, 147-162, 2004
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 Inform. 2004;15(2):201-10 pubmed
Araki Y, Konishi S, Imoto S Functional discriminant analysis for time-seriese gene expression data via radial basis function expansion Proc. COMPSTAT 2004. 613-62Physica-Verlag/Springer, 2004. (COMPSTAT2004: Refereed conference)
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
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 Proc Int Conf Intell Syst Mol Biol. 1995;3:359-66. pubmed
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
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
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 Inform. 2002;13:3-11. pubmed
Bannai H, Hyyro H, Shinohara A, Takeda M, Nakai K, Miyano S An O(N2) algorithm for discovering optimal Boolean pattern pairs IEEE/ACM Trans Comput Biol Bioinform. 2004 Oct-Dec;1(4):159-70. pubmed
Bannai H, Inenaga S, Shinohara A, Takeda M Inferring strings from graphs and arrays Proc. 28th International Symposium on Mathematical Foundations of Computer Science (MFCS2003). Lecture Notes in Computer Science, 2747, 208-217, 2003. (Peer-reviewed paper)
Bannai H, Inenaga S, Shinohara A, Takeda M, Miyano S Efficiently finding regulatory elements using correlation with gene expression J Bioinform Comput Biol. 2004 Jun;2(2):273-88. pubmed
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
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
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, Nakai K, Miyano S Extensive feature detection of N-terminal protein sorting signals Bioinformatics. 2002 Feb;18(2):298-305. pubmed
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
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 Pac Symp Biocomput. 2003:17-28. pubmed
De Hoon MJ, Imoto S, Kobayashi K, Ogasawara N, 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 MJ, Imoto S, Kobayashi K, Ogasawara N, Miyano S Predicting the operon structure of Bacillus subtilis using operon length, intergene distance, and gene expression information Pac Symp Biocomput. 2004:276-87 pubmed
De Hoon MJ, Imoto S, Miyano S Statistical analysis of a small set of time-ordered gene expression data using linear splines Bioinformatics. 2002 Nov;18(11):1477-85. pubmed
De Hoon MJ, Imoto S, Nolan J, Miyano S Open source clustering software. Bioinformatics, 20(9), 1453-1454, 2004
De Hoon MJ, 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. 2004 Aug 4;20 Suppl 1:i101-8. pubmed
De Hoon MJ, Makita Y, Nakai K, Miyano S Prediction of transcriptional terminators in Bacillus subtilis and related species PLoS Comput Biol. 2005 Aug;1(3):e25. Epub 2005 Aug 12. pubmed
Doi A, Fujita S, Matsuno H, Nagasaki M, Miyano S Constructing biological pathway models with hybrid functional Petri nets In Silico Biol. 2004;4(3):271-91 pubmed
Doi A, Nagasaki M, Fujita S, Matsuno H, Miyano S Genomic Object Net: II. Modelling biopathways by hybrid functional Petri net with extension Appl Bioinformatics. 2003;2(3):185-8. pubmed
Doi A, Nagasaki M, Matsuno H, Miyano S Simulation-based validation of the p53 transcriptional activity with hybrid functional petri net In Silico Biol. 2006;6(1-2):1-13. pubmed
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 Inform. 2006;17(1):112-23. pubmed
Fujita A, Sato JR, Garay-Malpartida HM, Yamaguchi R, Miyano S, Sogayar MC, Ferreira CE Modeling gene expression regulatory networks with the sparse vector autoregressive model BMC Syst Biol. 2007 Aug 30;1:39. pubmed
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
Furukawa N, Matsumoto S, Shinohara A, Shoudai T, Miyano S HAKKE: A multi-strategy prediction system for sequences Genome Informatics, 7, 98-107, 1996
Furuya S, Miyano S Analogy is NP-hard Proceedings of the Second Workshop on Algorithmic Learning Theory, 207-212, 1991
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 NP-hard aspects in analogical reasoning Bulletin of Informatics and Cybernetics, 25(3-4), 155-159, 1993
Gupta PK, 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
Hayashi T, Miyano S Finite tree automata on infinite trees Bulletin of Informatics and Cybernetics, 21(3-4), 71-82, 1985
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
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)
Hirose O, Yoshida R, Yamaguchi R, Imoto S, Higuchi T, Miyano S Clustering samples characterized by time course gene expression profiles using the mixture of state space models Genome Inform. 2007;18:258-66. pubmed
Imoto S 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, 2007
Imoto S, Goto T, Miyano S Estimation of genetic networks and functional structures between genes by using Bayesian networks and nonparametric regression Pac Symp Biocomput. 2002:175-86. pubmed
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
Imoto S, Higuchi T, Goto T, Tashiro K, Kuhara S, Miyano S Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks Proc IEEE Comput Soc Bioinform Conf. 2003;2:104-13. pubmed
J Bioinform Comput Biol. 2004 Mar;2(1):77-98. pubmed
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, 149-162004
Imoto S, Kim S, Goto T, Miyano S, Aburatani S, Tashiro K, Kuhara S Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network J Bioinform Comput Biol. 2003 Jul;1(2):231-52. pubmed
Imoto S, Konishi S Selection of smoothing parameters in B-spline nonparametric regression models using information criteria Annals of the Institute of Statistical Mathematics, 55(4), 671-687, 2003
Shimamura T, Imoto S, Yamaguchi R, Miyano S Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data Genome Inform. 2007;19:142-53. pubmed
Imoto S, Savoie CJ, Aburatani S, Kim S, Tashiro K, Kuhara S, Miyano S Use of gene networks for identifying and validating drug targets J Bioinform Comput Biol. 2003 Oct;1(3):459-74. pubmed
Imoto S, Tamada Y, Araki H, Yasuda K, Print CG, Charnock-Jones SD, Sanders D, Savoie CJ, Tashiro K, Kuhara S, Miyano S Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles Pac Symp Biocomput. 2006:559-71. pubmed
Imoto S, Tamada Y, Savoie CJ, Miyano S Analysis of gene networks for drug target discovery and validation Methods Mol Biol. 2007;360:33-56. pubmed
Inenaga S, Bannai H, Hyyro 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
Inenaga S, Bannai H, Shinohara A, Takeda M, Arikawa S Discovering best variable-length-don't-care patterns Proc. 5th International Conference on Discovery Science (DS2002). Lecture Notes in Computer Science, 2534: 86-97, 2002. (Peer-reviewed paper)
Inenaga S, Shinohara A, Takeda M, Bannai H, Arikawa S Space-economical construction of index structures for all-suffixes of a string Proc. 27th. International Symposium on Mathematical Foundation of Computer Science (MFCS2002), Lecture Notes in Computer Science, 242341-352, 2002. (Peer-reviewed paper)
Jeong E, Nagasaki M, Miyano S Conversion from BioPAX to CSO for system dynamics and visualization of biological pathway Genome Inform. 2007;18:225-36. pubmed
Jeong E, Nagasaki M, Saito A, Miyano S Cell system ontology: representation for modeling, visualizing, and simulating biological pathways In Silico Biol. 2007;7(6):623-38. pubmed
Jeong E, Chung IF, Miyano S A neural network method for identification of RNA-interacting residues in protein Genome Inform. 2004;15(1):105-16. pubmed
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
Kato M, Nagasaki M, Doi A, Miyano S Automatic drawing of biological networks using cross cost and subcomponent data Genome Inform. 2005;16(2):22-31. pubmed
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. 2004 Jul;75(1-3):57-65. pubmed
Kim SY, Imoto S, Miyano S Inferring gene networks from time series microarray data using dynamic Bayesian networks Brief Bioinform. 2003 Sep;4(3):228-35. pubmed
Kitakaze H, Matsuno H, Ikeda N, Miyano S Prediction of debacle points for robustness of biological pathways by using recurrent neural networks Genome Inform. 2005;16(1):192-202. pubmed
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 Mar 6;8:76. pubmed
Konishi S, Ando T, Imoto S Bayesian information criteria and smoothing parameter selection in radial basis function networks Biometrika, 91(1), 27-43, 2003
Li C, Ge QW, Nakata M, Matsuno H, Miyano S Modelling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets J Biosci. 2007 Jan;32(1):113-27. pubmed
Li C, Suzuki S, Ge QW, Nakata M, Matsuno H, Miyano S Structural modeling and analysis of signaling pathways based on Petri nets J Bioinform Comput Biol. 2006 Oct;4(5):1119-40. pubmed
Makita Y, De Hoon MJ, Ogasawara N, Miyano S, Nakai K Bayesian joint prediction of associated transcription factors in Bacillus subtilis Pac Symp Biocomput. 2005:507-18. pubmed
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, Miyano S Design sspects of discovery systems IEICE Transactions on Information and Systems, E83-D(1), 61-70, 2000
Maruyama O, Miyano S Inferring a tree from walks Theoretical Computer Science, 161(1-2), 289-300, 1996
Maruyama O, Miyano S Taking a walk on a graph Mathematica Japonica, 43(3), 595-606, 1996
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
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
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
Maruyama O, Uchida T, Sim KL, 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
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
Matsuno H, Doi A, Hirata Y, Miyano S XML documentation of biopathways and their simulations in Genomic Object Net Genome Inform. 2001;12:54-62. pubmed
Matsuno H, Doi A, Nagasaki M, Miyano S Hybrid Petri net representation of gene regulatory network Pac Symp Biocomput. 2000:341-52. pubmed
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
Matsuno H, Inouye ST, Okitsu Y, Fujii Y, Miyano S A new regulatory interaction suggested by simulations for circadian genetic control mechanism in mammals J Bioinform Comput Biol. 2006 Feb;4(1):139-53. pubmed
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
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 Pac Symp Biocomput. 2003:152-63. pubmed
Matsuno H, Tanaka Y, Aoshima H, Doi A, Matsui M, Miyano S Biopathways representation and simulation on hybrid functional Petri net In Silico Biol. 2003;3(3):389-404. pubmed
Miyano S A hierarchy theorem for multihead stack-counter automata Acta Informatica, 17(1), 63-67, 1982
Miyano S A parallelizable lexicographically first edge-induced subgraph problem Information Processing Letters, 27(2), 75-78, 1988
Miyano S Computational systems biology Proc. Third International Conference on Information (Li, L. and Yen, K.K., Eds.), 9-14, 2004
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
Miyano S Indexing alternating finite automata and binary tree like circuits Bulletin of Informatics and Cybernetics, 23(1-2), 79-88, 1988
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
Miyano S Learning theory towards genome informatics IEICE Transactions on Information and Systems, E78-D(5), 560-567, 1995
Proc. 4th International Workshop on Algorithmic Learning Theory, Lecture Notes in Computer Science, 744: 19-36, 1993
Miyano S On a lower bound of Shepherdson function Memoirs of the Faculty of Science, Kyushu University, Ser. A. 33(2), 257-267, 1979
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
Miyano S One-way weak-stack-counter automata Journal of Computer and System Sciences, 20(1), 59-76, 1980
Miyano S Parallel complexity and P-complete problems Proceedings of International Conference on Fifth Generation Computer Systems 1988, 532-541, 1988
Miyano S Remarks on multihead pushdown automata and multihead stack automata Journal of Computer and System Sciences, 27(1), 116-124, 1983
Miyano S Remarks on two-way automata with weak-counters Information Processing Letters, 18(2), 105-107, 1984
Miyano S Systematized approaches to the complexity of subgraph problems Journal of Information Processing, 13(4), 442-448, 1990
Miyano S The lexicographically first maximal subgraph problems - P-completeness and NC algorithms Mathematical Systems Theory, 22(1), 47-73, 1989
Miyano S Two-way deterministic multi-weak-counter machines Theoretical Computer Science. 21(1):27-32, 1982
Miyano S ΔP2-complete lexicographically first maximal subgraph problems Theoretical Computer Science, 88(1), 33-57, 1991
Miyano S, Haraguchi M Recovery of incomplete tables under functional dependencies Bulletin of Informatics and Cybernetics, 20(1-2), 25-41, 1982
Miyano S, Hayashi T Alternating finite automata on ω-words Theoretical Computer Science, 32(3), 321-330, 1984
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
Miyano S, Shinohara A, Shinohara T Polynomial-time learning of elementary formal systems New Generation Computing, 18(3), 217-242, 2000
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
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 Inform Ser Workshop Genome Inform. 1999;10:186-195. pubmed
Nagasaki M, Doi A, Matsuno H, Miyano S Genomic Object Net: I. A platform for modelling and simulating biopathways Appl Bioinformatics. 2003;2(3):181-4. pubmed
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 Inform. 2006;17(1):46-61. pubmed
Nagasaki M, Doi A, Matsuno H, Miyano S A versatile petri net based architecture for modeling and simulation of complex biological processes Genome Inform. 2004;15(1):180-97. pubmed
Nagasaki M, Doi A, Matsuno H, Miyano S Computational modeling of biological processes with Petri net based architecture Bioinformatics Technologies (Y.P. Chen, ed). 179-242, 2005
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 Petri net modeling of biological pathways Proc. Algebraic Biology 20(Universal Academy Press), 19-31, 2005
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, 168-169, 2003
Nagasaki M, Onami S, Miyano S, Kitano H Bio-calculus: Its Concept and Molecular Interaction Genome Inform Ser Workshop Genome Inform. 1999;10:133-143. pubmed
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
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
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
Nakayashiki T, Ebihara K, Bannai H, Nakamura Y Yeast [PSI+] "prions" that are crosstransmissible and susceptible beyond a species barrier through a quasi-prion state Mol Cell. 2001 Jun;7(6):1121-30. pubmed
Nariai N, Kim S, Imoto S, Miyano S Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks Pac Symp Biocomput. 2004:336-47. pubmed
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. 2005 Sep 1;21 Suppl 2:ii206-12. pubmed
Noda K, Shinohara A, Takeda M, Matsumoto S, Miyano S, Kuhara S Finding Genetic Network from Experiments by Weighted Network Model Genome Inform Ser Workshop Genome Inform. 1998;9:141-150. pubmed
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)
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. 2003;48(6):293-9. Epub 2003 May 10. pubmed
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. 2005;50(1):30-5. Epub 2004 Dec 14. pubmed
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. (20Workshop on Pattern Recognition In Bioinformatics (PRIB'06))
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
Ott S, Hansen A, Kim SY, Miyano S Superiority of network motifs over optimal networks and an application to the revelation of gene network evolution Bioinformatics. 2005 Jan 15;21(2):227-38. Epub 2004 Sep 17. pubmed
Ott S, Imoto S, Miyano S Finding optimal models for small gene networks Pac Symp Biocomput. 2004:557-67. pubmed
Ott S, Miyano S Finding optimal gene networks using biological constraints Genome Inform. 2003;14:124-33. pubmed
Ott S, Tamada Y, Bannai H, Nakai K, Miyano S Intrasplicing--analysis of long intron sequences Pac Symp Biocomput. 2003:339-50. pubmed
Saito A, Nagasaki M, Doi A, Ueno K, Miyano S Cell fate simulation model of gustatory neurons with MicroRNAs double-negative feedback loop by hybrid functional Petri net with extension Genome Inform. 2006;17(1):100-11. pubmed
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. 2007 Jan 18;8:15. pubmed
Savoie CJ, 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 Res. 2003 Feb 28;10(1):19-25. pubmed
Shimamura T, Imoto S, Yamaguchi R, Miyano S Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data Genome Inform. 2007;19:142-53. pubmed
Shimozono S, Miyano S Complexity of finding alphabet indexing IEICE Transactions on Information and Systems, E78-D(1), 13-18, 1995
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
Shinohara A, Miyano S Teachability in computational learning New Generation Computing, 8(4), 337-347, 1991
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, 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 Proc Int Conf Intell Syst Mol Biol. 1995;3:359-66. pubmed
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
Shoudai T, Miyano S Using maximal independent sets to solve problems in parallel Theoretical Computer Science, 148(1), 57-65, 1995
Sim KL, Uchida T, Miyano S ProDDO: a database of disordered proteins from the Protein Data Bank (PDB) Bioinformatics. 2001 Apr;17(4):379-80. pubmed
Standley DM, Yamashita R, Kinjo AR, Toh H, Nakamura H SeSAW: balancing sequence and structural information in protein functional mapping Bioinformatics. 2010 May 1;26(9):1258-9. doi: 10.1093/bioinformatics/btq116. Epub 2010 Mar 17. pubmed
Sugii M, Okada R, Matsuno H, Miyano S Performance improvement in protein N-myristoyl classification by BONSAI with insignificant indexing symbol Genome Inform. 2007;18:277-86. pubmed
Sumii E, Bannai H The extension of ML with hypothetical views for discovery science: formalization and implementation Journal of Functional and Logic Programming, Vol.2003, Special Issue 1, 2003
Sumii E, Bannai H VMlambda: a functional calculus for scientific discovery Proc. 6th International Symposium on Functional and Logic Programming (FLOPS 2002), Lecture Notes in Computer Science, 2441, 290-304, 2002. (Peer-reviewed paper)
Takeda M, Inenaga S, Bannai H, Shinohara A, Arikawa S Discovering most classificatory patterns for very expressive pattern classes Proc. 6th International Conference on Discovery Science (DS 2003), Lecture Notes in Computer Science, 2843, 486-493, 2003. (Peer-reviewed paper)
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. 2002 Mar;70(3):781-6. Epub 2002 Feb 1. pubmed
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 Lett. 2004 Jan 2;556(1-3):53-8. pubmed
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 Exp Zool A Comp Exp Biol. 2006 Sep 1;305(9):787-98. pubmed
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 Bioinform Comput Biol. 2005 Dec;3(6):1295-313. pubmed
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
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 Bioinform Comput Biol. 2005 Dec;3(6):1295-313. pubmed
Tamada Y, Imoto S, Tashiro K, Kuhara S, Miyano S Identifying drug active pathways from gene networks estimated by gene expression data Genome Inform. 2005;16(1):182-91. pubmed
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. 2003 Oct;19 Suppl 2:ii227-36. pubmed
Tanaka M, Nakazono S, Matsuno H, Tsujimoto H, Kitamura Y, Miyano S Intelligent system for topic survey in MEDLINE by keyword recommendation and learning text characteristics Genome Inform Ser Workshop Genome Inform. 2000;11:73-82. pubmed
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 Inform. 2006;17(2):226-38. pubmed
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
Tateishi E, Miyano S A greedy strategy for finding motifs from yes-no examples Pac Symp Biocomput. 1996:599-613. pubmed
Termier A, Tamada Y, Imoto S, Washio T, Higuchi T From closed tree mining towards closed DAG mining Proc. International Workshop on Data Mining and Statistical Science, 1-7, 2006. (Peer-reviewed conference paper)
Termier A, Tamada Y, Numata K, Imoto S, Washio T, Higuchi T DIGDAG, a first algorithm to mine closed frequent embedded sub-DAGs Proc. 5th International Workshop on Mining and Learning with Graphs. CR-ROM, 2007. (MLG2007: Refereed conference). (Peer-reviewed conference paper)
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
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
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
Usuzaka Si, Sim KL, 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 Inform Ser Workshop Genome Inform. 1998;9:91-101. pubmed
Washio T, Higuchi T, Imoto S, Tamada Y, Sato K, Motoda H Graph mining and its application to statistical modeling (in Japanese with English abstract) Proc. Inst. Statist. Math, 54(2), 315-332, 2006
Yamaguchi A, Nakano K, Miyano S An approximation algorithm for the minimum common supertree problem Nordic J. Computing, 4(2), 303-316, 1997
Yamaguchi R, Yamamoto M, Imoto S, Nagasaki M, Yoshida R, Tsuiji K, Ishige A, Asou H, Watanabe K, Miyano S Identification of activated transcription factors from microarray gene expression data of Kampo medicine-treated mice Genome Inform. 2007;18:119-29. pubmed
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
Yasuda T, Bannai H, Onami S, Miyano S, Kitano H Towards Automatic Construction of Cell-Lineage of C. elegans from Nomarski DIC Microscope Images Genome Inform Ser Workshop Genome Inform. 1999;10:144-154. pubmed
Yoshida R, Higuchi T, Imoto S A mixed factors model for dimension reduction and extraction of a group structure in gene expression data Proc IEEE Comput Syst Bioinform Conf. 2004:161-72. pubmed
Yoshida R, Higuchi T, Imoto S, Miyano S ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profilesBioinformatics. 2006 Jun 15;22(12):1538-9. Epub 2006 Apr 10. pubmed
Yoshida R, Imoto S, Higuchi T 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, 2005. (DMBio2005: Refereed conference)
Yoshida R, Imoto S, Higuchi T Estimating time-dependent gene networks from time series microarray data by dynamic linear models with Markov switching Proc IEEE Comput Syst Bioinform Conf. 2005:289-98. pubmed
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 Inform. 2006;17(1):88-99. pubmed
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)
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