2009 | ||
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36 | EE | Satoru Miyano, Rui Yamaguchi, Yoshinori Tamada, Masao Nagasaki, Seiya Imoto: Gene Networks Viewed through Two Models. BICoB 2009: 54-66 |
2008 | ||
35 | EE | Osamu Hirose, Ryo Yoshida, Rui Yamaguchi, Seiya Imoto, Tomoyuki Higuchi, Satoru Miyano: Analyzing Time Course Gene Expression Data with Biological and Technical Replicates to Estimate Gene Networks by State Space Models. Asia International Conference on Modelling and Simulation 2008: 940-946 |
34 | EE | Ryo Yoshida, Masao Nagasaki, Rui Yamaguchi, Seiya Imoto, Satoru Miyano, Tomoyuki Higuchi: Bayesian learning of biological pathways on genomic data assimilation. Bioinformatics 24(22): 2592-2601 (2008) |
33 | EE | Osamu Hirose, Ryo Yoshida, Seiya Imoto, Rui Yamaguchi, Tomoyuki Higuchi, Stephen D. Charnock-Jones, Cristin G. Print, Satoru Miyano: 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) |
2007 | ||
32 | EE | Kazuyuki Numata, Seiya Imoto, Satoru Miyano: A Structure Learning Algorithm for Inference of Gene Networks from Microarray Gene Expression Data Using Bayesian Networks. BIBE 2007: 1280-1284 |
31 | EE | Ryo Yoshida, Kazuyuki Numata, Seiya Imoto, Masao Nagasaki, Atsushi Doi, Kazuko Ueno, Satoru Miyano: Computational Genome-Wide Discovery of Aberrant Splice Variations with Exon Expression Profiles. BIBE 2007: 715-722 |
30 | EE | Pramod K. Gupta, Ryo Yoshida, Seiya Imoto, Rui Yamaguchi, Satoru Miyano: Statistical Absolute Evaluation of Gene Ontology Terms with Gene Expression Data. ISBRA 2007: 146-157 |
29 | EE | Alexandre Termier, Yoshinori Tamada, Kazuyuki Numata, Seiya Imoto, Takashi Washio, Tomoyuki Higuchi: DIGDAG, a First Algorithm to Mine Closed Frequent Embedded Sub-DAGs. MLG 2007 |
2006 | ||
28 | EE | Seiya Imoto, Yoshinori Tamada, Hiromitsu Araki, Kaori Yasuda, Cristin G. Print, Stephen D. Charnock-Jones, Deborah Sanders, Christopher J. Savoie, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Computational Strategy for Discovering Druggable Gene Networks from Genome-Wide RNA Expression Profiles. Pacific Symposium on Biocomputing 2006: 559-571 |
27 | EE | Ryo Yoshida, Tomoyuki Higuchi, Seiya Imoto, Satoru Miyano: ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles. Bioinformatics 22(12): 1538-1539 (2006) |
26 | EE | Reiichiro Nakamichi, Seiya Imoto, Satoru Miyano: Statistical Model Selection Method to Analyze Combinatorial Effects of Snps and Environmental Factors for Binary Disease. International Journal on Artificial Intelligence Tools 15(5): 711-724 (2006) |
2005 | ||
25 | EE | Ryo Yoshida, Seiya Imoto, Tomoyuki Higuchi: Estimating Time-Dependent Gene Networks from Time Series Microarray Data by Dynamic Linear Models with Markov Switching. CSB 2005: 289-298 |
24 | EE | Naoki Nariai, Yoshinori Tamada, Seiya Imoto, Satoru Miyano: Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data. ECCB/JBI 2005: 212 |
23 | EE | Osamu Hirose, Naoki Nariai, Yoshinori Tamada, Hideo Bannai, Seiya Imoto, Satoru Miyano: Estimating Gene Networks from Expression Data and Binding Location Data via Boolean Networks. ICCSA (3) 2005: 349-356 |
22 | EE | Ryo Yoshida, Seiya Imoto, Tomoyuki Higuchi: A Penalized Likelihood Estimation on Transcriptional Module-Based Clustering. ICCSA (3) 2005: 389-401 |
21 | EE | Yoshinori Tamada, Hideo Bannai, Seiya Imoto, Toshiaki Katayama, Minoru Kanehisa, Satoru Miyano: Utilizing Evolutionary Information and Gene Expression Data for Estimating Gene Networks with Bayesian Network Models. J. Bioinformatics and Computational Biology 3(6): 1295-1314 (2005) |
2004 | ||
20 | EE | Reiichiro Nakamichi, Seiya Imoto, Satoru Miyano: Case-Control Study of Binary Disease Trait Considering Interactions between SNPs and Environmental Effects using Logistic Regression. BIBE 2004: 73-78 |
19 | EE | Seiya Imoto, Tomoyuki Higuchi, SunYong Kim, Euna Jeong, Satoru Miyano: Residual Bootstrapping and Median Filtering for Robust Estimation of Gene Networks from Microarray Data. CMSB 2004: 149-160 |
18 | EE | Ryo Yoshida, Tomoyuki Higuchi, Seiya Imoto: A Mixed Factors Model for Dimension Reduction and Extraction of a Group Structure in Gene Expression Data. CSB 2004: 161-172 |
17 | EE | Michiel J. L. de Hoon, Yuko Makita, Seiya Imoto, Kazuo Kobayashi, Naotake Ogasawara, Kenta Nakai, Satoru Miyano: Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data. ISMB/ECCB (Supplement of Bioinformatics) 2004: 101-108 |
16 | EE | Tomohiro Ando, Seiya Imoto, Satoru Miyano: Functional Data Analysis of the Dynamics of Gene Regulatory Networks. KELSI 2004: 69-83 |
15 | EE | Michiel J. L. de Hoon, Seiya Imoto, Kazuo Kobayashi, Naotake Ogasawara, Satoru Miyano: Predicting the Operon Structure of Bacillus subtilis Using Operon Length, Intergene Distance, and Gene Expression Information. Pacific Symposium on Biocomputing 2004: 276-287 |
14 | EE | Naoki Nariai, SunYong Kim, Seiya Imoto, Satoru Miyano: Using Protein-Protein Interactions for Refining Gene Networks Estimated from Microarray Data by Bayesian Networks. Pacific Symposium on Biocomputing 2004: 336-347 |
13 | EE | Sascha Ott, Seiya Imoto, Satoru Miyano: Finding Optimal Models for Small Gene Networks. Pacific Symposium on Biocomputing 2004: 557-567 |
12 | EE | Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks. J. Bioinformatics and Computational Biology 2(1): 77-98 (2004) |
2003 | ||
11 | EE | SunYong Kim, Seiya Imoto, Satoru Miyano: Dynamic Bayesian Network and Nonparametric Regression for Nonlinear Modeling of Gene Networks from Time Series Gene Expression Data. CMSB 2003: 104-113 |
10 | EE | Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks. CSB 2003: 104-113 |
9 | Yoshinori Tamada, SunYong Kim, Hideo Bannai, Seiya Imoto, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection. ECCB 2003: 227-236 | |
8 | EE | Michiel J. L. de Hoon, Seiya Imoto, Kazuo Kobayashi, Naotake Ogasawara, Satoru Miyano: Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data of Bacillus Subtilis Using Differential Equations. Pacific Symposium on Biocomputing 2003: 17-28 |
7 | SunYong Kim, Seiya Imoto, Satoru Miyano: Inferring gene networks from time series microarray data using dynamic Bayesian networks. Briefings in Bioinformatics 4(3): 228 (2003) | |
6 | EE | Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Aburatani, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network. J. Bioinformatics and Computational Biology 1(2): 231-252 (2003) |
5 | EE | Seiya Imoto, Christopher J. Savoie, Sachiyo Aburatani, SunYong Kim, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Use of Gene Networks for Identifying and Validating Drug Targets. J. Bioinformatics and Computational Biology 1(3): 459-474 (2003) |
2002 | ||
4 | EE | Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Aburatani, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano: Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network. CSB 2002: 219-227 |
3 | EE | Michiel J. L. de Hoon, Seiya Imoto, Satoru Miyano: Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data Using Differential Equations. Discovery Science 2002: 267-274 |
2 | EE | Seiya Imoto, Takao Goto, Satoru Miyano: Estimation of Genetic Networks and Functional Structures Between Genes by Using Bayesian Networks and Nonparametric Regression. Pacific Symposium on Biocomputing 2002: 175-186 |
1 | Michiel J. L. de Hoon, Seiya Imoto, Satoru Miyano: Statistical analysis of a small set of time-ordered gene expression data using linear splines. Bioinformatics 18(11): 1477-1485 (2002) |