Seiya Imoto

发表

Sparse Overlapping Group Lasso for Integrative Multi-Omics Analysis

Satoru Miyano, Heewon Park, Atsushi Niida, 2015, J. Comput. Biol..

OVarCall: Bayesian Mutation Calling Method Utilizing Overlapping Paired-End Reads.

Satoru Miyano, Yuichi Shiraishi, Seiya Imoto, 2017, IEEE transactions on nanobioscience.

Identifying Hidden Confounders in Gene Networks by Bayesian Networks

Masato Inoue, Satoru Miyano, Seiya Imoto, 2010, 2010 IEEE International Conference on BioInformatics and BioEngineering.

Parallel agent-based simulator for influenza pandemic

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2011, AAMAS'11.

Computational Drug Target Pathway Discovery: A Bayesian Network Approach

Satoru Miyano, Seiya Imoto, Yoshinori Tamada, 2011, Handbook of Statistical Bioinformatics.

Additional file 1 of Sequence-specific bias correction for RNA-seq data using recurrent neural networks

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2017 .

Estimating time-dependent gene networks from time series microarray data by dynamic linear models with Markov switching

Tomoyuki Higuchi, Seiya Imoto, Ryo Yoshida, 2005, 2005 IEEE Computational Systems Bioinformatics Conference (CSB'05).

Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data Using Differential Equations

Satoru Miyano, Seiya Imoto, Michiel J. L. de Hoon, 2002, Discovery Science.

An Efficient Data Assimilation Schema for Restoration and Extension of Gene Regulatory Networks Using Time-Course Observation Data

Satoru Miyano, Tatsuya Akutsu, Tomoya Mori, 2014, J. Comput. Biol..

Discovering functional gene pathways associated with cancer heterogeneity via sparse supervised learning

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2010, 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Unraveling Dynamic Activities of Autocrine Pathways that Control Drug-Response Transcriptome Networks

Deborah Sanders, Masao Nagasaki, Atsushi Doi, 2008, Pacific Symposium on Biocomputing.

Estimation of macroscopic parameter in agent-based pandemic simulation

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2011, 14th International Conference on Information Fusion.

Predicting Japanese Kampo formulas by analyzing database of medical records: a preliminary observational study

Hideki Mima, Satoru Miyano, Kenji Watanabe, 2016, BMC Medical Informatics and Decision Making.

Parallel Algorithm for Learning Optimal Bayesian Network Structure

Satoru Miyano, Seiya Imoto, Yoshinori Tamada, 2011, J. Mach. Learn. Res..

Gene Networks Viewed through Two Models

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2009, BICoB.

Gene set-based module discovery in the breast cancer transcriptome

Michael Q. Zhang, Andrew D. Smith, Atsushi Niida, 2009, BMC Bioinformatics.

Genomic data assimilation using a higher moment filtering technique for restoration of gene regulatory networks

Satoru Miyano, Tatsuya Akutsu, Teppei Shimamura, 2015, BMC Systems Biology.

Poster: Comprehensive pharmacogenomic pathway screening by data assimilation

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2011, 2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences (ICCABS).

Dynamic Bayesian Network and Nonparametric Regression for Nonlinear Modeling of Gene Networks from Time Series Gene Expression Data

Satoru Miyano, Seiya Imoto, SunYong Kim, 2003, CMSB.

A mixed factors model for dimension reduction and extraction of a group structure in gene expression data

Tomoyuki Higuchi, Seiya Imoto, Ryo Yoshida, 2004, Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004..

Parameter estimation in multi-compartment SIR model

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2014, 17th International Conference on Information Fusion (FUSION).

A Structure Learning Algorithm for Inference of Gene Networks from Microarray Gene Expression Data Using Bayesian Networks

Satoru Miyano, Seiya Imoto, Kazuyuki Numata, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks

Satoru Miyano, Tomoyuki Higuchi, Satoru Kuhara, 2004, J. Bioinform. Comput. Biol..

Adaptive NetworkProfiler for Identifying Cancer Characteristic-Specific Gene Regulatory Networks

Satoru Miyano, Teppei Shimamura, Heewon Park, 2018, J. Comput. Biol..

A feature selection method using fixed-point algorithm for DNA microarray gene expression data

Kuldip K. Paliwal, Satoru Miyano, Alok Sharma, 2014, Int. J. Knowl. Based Intell. Eng. Syst..

A between-Class Overlapping Filter-Based Method for transcriptome Data Analysis

Satoru Miyano, Alok Sharma, Seiya Imoto, 2012, J. Bioinform. Comput. Biol..

Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data.

Satoru Miyano, Seiya Imoto, Sun Yong Kim, 2004 .

Analyzing Time Course Gene Expression Data with Biological and Technical Replicates to Estimate Gene Networks by State Space Models

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2008, 2008 Second Asia International Conference on Modelling & Simulation (AMS).

A strategy to select suitable physicochemical attributes of amino acids for protein fold recognition

Kuldip K. Paliwal, Satoru Miyano, James G. Lyons, 2013, BMC Bioinformatics.

Estimation of Genetic Networks and Functional Structures Between Genes by Using Bayesian Networks and Nonparametric Regression

Satoru Miyano, Seiya Imoto, Takao Goto, 2001, Pacific Symposium on Biocomputing.

Intra-bin structural variant segmentation for whole-genome sequencing data using U-net

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2019 .

Functional Data Analysis of the Dynamics of Gene Regulatory Networks

Satoru Miyano, Seiya Imoto, Tomohiro Ando, 2004, KELSI.

Bayesian learning of biological pathways on genomic data assimilation

Masao Nagasaki, Satoru Miyano, Tomoyuki Higuchi, 2008, Bioinform..

Gene set differential analysis of time course expression profiles via sparse estimation in functional logistic model with application to time-dependent biomarker detection.

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2016, Biostatistics.

Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data of Bacillus Subtilis Using Differential Equations

Satoru Miyano, Seiya Imoto, Michiel J. L. de Hoon, 2002, Pacific Symposium on Biocomputing.

Combining Gene Expression Data with DNA Sequence Information for Estimating Gene Networks Using Bayesian Network Model

Sun Yong Kim, Satoru Miyano, Hideo Bannai, 2003 .

A filter based feature selection algorithm using null space of covariance matrix for DNA microarray gene expression data

Satoru Miyano, Alok Sharma, Seiya Imoto, 2012 .

Interaction-Based Feature Selection for Uncovering Cancer Driver Genes Through Copy Number-Driven Expression Level

Satoru Miyano, Heewon Park, Atsushi Niida, 2017, J. Comput. Biol..

A Penalized Likelihood Estimation on Transcriptional Module-Based Clustering

Tomoyuki Higuchi, Seiya Imoto, Ryo Yoshida, 2005, ICCSA.

Genetic algorithm for an optimized weighted voting scheme incorporating k-separated bigram transition probabilities to improve protein fold recognition

Kuldip K. Paliwal, Satoru Miyano, Abdollah Dehzangi, 2014, Asia-Pacific World Congress on Computer Science and Engineering.

Residual Bootstrapping and Median Filtering for Robust Estimation of Gene Networks from Microarray Data

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2004, CMSB.

A likelihood-free filtering method via approximate Bayesian computation in evaluating biological simulation models

Satoru Miyano, Tatsuya Akutsu, Teppei Shimamura, 2016, Comput. Stat. Data Anal..

Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network

Satoru Miyano, Satoru Kuhara, Seiya Imoto, 2003, J. Bioinform. Comput. Biol..

Comprehensive Pharmacogenomic Pathway Screening by Data Assimilation

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2011, ISBRA.

Recursive regularization for inferring gene networks from time-course gene expression profiles

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2009, BMC Systems Biology.

A state space representation of VAR models with sparse learning for dynamic gene networks.

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2010, Genome informatics. International Conference on Genome Informatics.

Estimation of abrupt changes in sentinel observation data of influenza epidemics in Japan

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2013, Proceedings of the 16th International Conference on Information Fusion.

HapMuC: somatic mutation calling using heterozygous germ line variants near candidate mutations

Yusuke Sato, Satoru Miyano, Yuichi Shiraishi, 2014, Bioinform..

Estimating Gene Networks from Expression Data and Binding Location Data via Boolean Networks

Satoru Miyano, Hideo Bannai, Seiya Imoto, 2005, ICCSA.

Robust Sample-Specific Stability Selection with Effective Error Control

Satoru Miyano, Makoto Yamada, Heewon Park, 2019, J. Comput. Biol..

Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks

Satoru Miyano, Tomoyuki Higuchi, Satoru Kuhara, 2003, Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003.

Identifying Gene Pathways Associated with Cancer Characteristics via Sparse Statistical Methods

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Collocation-based sparse estimation for constructing dynamic gene networks.

Masao Nagasaki, Satoru Miyano, André Fujita, 2010, Genome informatics. International Conference on Genome Informatics.

DIGDAG, a First Algorithm to Mine Closed Frequent Embedded Sub-DAGs

Alexandre Termier, Takashi Washio, Tomoyuki Higuchi, 2007, MLG.

A Novel Adaptive Penalized Logistic Regression for Uncovering Biomarker Associated with Anti-Cancer Drug Sensitivity

Satoru Miyano, Yuichi Shiraishi, Heewon Park, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Binary Contingency Table Method for Analyzing Gene Mutation in Cancer Genome

Satoru Miyano, Atsushi Niida, Seiya Imoto, 2015, ISBRA.

Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.

Masao Nagasaki, Atsushi Doi, Hiroshi Matsuno, 2006, Genome informatics. International Conference on Genome Informatics.

OVarCall: Bayesian Mutation Calling Method Utilizing Overlapping Paired-End Reads

Satoru Miyano, Yuichi Shiraishi, Seiya Imoto, 2017, IEEE Transactions on NanoBioscience.

Network-Based Predictions and Simulations by Biological State Space Models: Search for Drug Mode of Action

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2010, Journal of Computer Science and Technology.

Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection

Satoru Miyano, Hideo Bannai, Satoru Kuhara, 2003, ECCB.

Cost-effective length and timing of school closure during an influenza pandemic depend on the severity

Seiya Imoto, Rui Yamaguchi, Shinji Nakaoka, 2013, Theoretical Biology and Medical Modelling.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2012, BMC Genomics.

Sign: large-scale gene network estimation environment for high performance computing.

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2011, Genome informatics. International Conference on Genome Informatics.

Binary contingency table method for analysing gene mutation in cancer genome

Satoru Miyano, Atsushi Niida, Seiya Imoto, 2016, Int. J. Bioinform. Res. Appl..

Connection between traditional medicine and disease

Kenji Watanabe, Seiya Imoto, Rui Yamaguchi, 2012, SIGH.

Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data.

Satoru Miyano, Teppei Shimamura, Seiya Imoto, 2007, Genome informatics. International Conference on Genome Informatics.

Null space based feature selection method for gene expression data

Satoru Miyano, Alok Sharma, Vandana Sharma, 2012, Int. J. Mach. Learn. Cybern..

Finding Optimal Models for Small Gene Networks

Satoru Miyano, Sascha Ott, Seiya Imoto, 2003 .

Gene Networks: Estimation, Modeling, and Simulation

Hiroshi Matsuno, Satoru Miyano, Seiya Imoto, 2014 .

Utilizing Evolutionary Information and Gene Expression Data for Estimating Gene Networks with Bayesian Network Models

Satoru Miyano, Hideo Bannai, Seiya Imoto, 2005, J. Bioinform. Comput. Biol..

Discovery of Exogenous Variables in Data with More Variables Than Observations

Aapo Hyvärinen, Teppei Shimamura, Takashi Washio, 2009, ICANN.

Multi-omics Approach for Estimating Metabolic Networks Using Low-Order Partial Correlations

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2013, J. Comput. Biol..

Statistical Absolute Evaluation of Gene Ontology Terms with Gene Expression Data

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2007, ISBRA.

Protein Fold Recognition Using Genetic Algorithm Optimized Voting Scheme and Profile Bigram

Abdollah Dehzangi, Alok Sharma, Sunil Pranit Lal, 2016, J. Softw..

ADAPTIVE LEARNING MACHINES FOR NONLINEAR CLASSIFICATION AND BAYESIAN INFORMATION CRITERIA

Seiya Imoto, 井元清哉, Tomohiro Ando, 2004 .

Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data

Satoru Miyano, Kenta Nakai, Seiya Imoto, 2004, ISMB/ECCB.

Computational gene network analysis reveals TNF-induced angiogenesis

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2012, BMC Systems Biology.

Inferring gene networks from time series microarray data using dynamic Bayesian networks

Satoru Miyano, Seiya Imoto, SunYong Kim, 2003, Briefings Bioinform..

Bayesian Network Approach to Estimate Gene Networks

Satoru Miyano, Seiya Imoto, 2007 .

Finding Gene Networks with

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2007 .

Searching Optimal Bayesian Network Structure on Constraint Search Space: Super-Structure Approach

Satoru Miyano, Seiya Imoto, Eric Perrier, 2010, JSAI-isAI Workshops.

Chapter 11 – Gene Networks: Estimation, Modeling, and Simulation

Satoru Miyano, Seiya Imoto, S. Miyano, 2006 .

Case-control study of binary disease trait considering interactions between SNPs and environmental effects using logistic regression

Satoru Miyano, Seiya Imoto, Reiichiro Nakamichi, 2004, Proceedings. Fourth IEEE Symposium on Bioinformatics and Bioengineering.

Estimation of nonlinear gene regulatory networks via L1 regularized NVAR from time series gene expression data.

Satoru Miyano, André Fujita, Teppei Shimamura, 2008, Genome informatics. International Conference on Genome Informatics.

ALPHLARD-NT: Bayesian Method for Human Leukocyte Antigen Genotyping and Mutation Calling through Simultaneous Analysis of Normal and Tumor Whole-Genome Sequence Data

Satoru Miyano, Seiya Imoto, Takuya Moriyama, 2019, J. Comput. Biol..

Computational Genome-Wide Discovery of Aberrant Splice Variations with Exon Expression Profiles

Masao Nagasaki, Atsushi Doi, Satoru Miyano, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

A Visualization Tool for Gene Network Discovery-G.NET

Sun Yong Kim, Satoru Miyano, Seiya Imoto, 2002 .

Predicting the Operon Structure of Bacillus subtilis Using Operon Length, Intergene Distance, and Gene Expression Information

Satoru Miyano, Seiya Imoto, Michiel J. L. de Hoon, 2003, Pacific Symposium on Biocomputing.

Identifiability of local transmissibility parameters in agent-based pandemic simulation

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2012, 2012 15th International Conference on Information Fusion.

SiGN-SSM: open source parallel software for estimating gene networks with state space models

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2011, Bioinform..

A mixed factors model for dimension reduction and extraction of a group structure in gene expression data

Seiya Imoto, Ryo Yoshida, Tomoyuki Higuchi, 2004 .

Use of Gene Networks for Identifying and Validating Drug Targets

Satoru Miyano, Satoru Kuhara, Seiya Imoto, 2003, J. Bioinform. Comput. Biol..

Gene regulatory network clustering for graph layout based on microarray gene expression data.

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2010, Genome informatics. International Conference on Genome Informatics.

Statistical model-based testing to evaluate the recurrence of genomic aberrations

Satoru Miyano, Teppei Shimamura, Atsushi Niida, 2012, Bioinform..

Multilayer Cluster Heat Map Visualizing Biological Tensor Data

Satoru Miyano, Atsushi Niida, Seiya Imoto, 2013, BSB.

Analysis of questionnaire for traditional medical and develop decision support system

Satoru Miyano, Kenji Watanabe, Seiya Imoto, 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops.

Estimating exogenous variables in data with more variables than observations

Aapo Hyvärinen, Teppei Shimamura, Takashi Washio, 2011, Neural Networks.

Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure

Satoru Miyano, Seiya Imoto, Eric Perrier, 2010, J. Mach. Learn. Res..

A Bayesian model integration for mutation calling through data partitioning

Satoru Miyano, Yuichi Shiraishi, Seiya Imoto, 2019, Bioinform..

Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data

Satoru Miyano, Seiya Imoto, Yoshinori Tamada, 2005, ECCB/JBI.

A Top-r Feature Selection Algorithm for Microarray Gene Expression Data

Satoru Miyano, Alok Sharma, Seiya Imoto, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Statistical Model Selection Method to Analyze Combinatorial Effects of Snps and Environmental Factors for Binary Disease

Satoru Miyano, Seiya Imoto, Reiichiro Nakamichi, 2006, Int. J. Artif. Intell. Tools.

Reconstruction of high read-depth signals from low-depth whole genome sequencing data using deep learning

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network

Satoru Miyano, Satoru Kuhara, Seiya Imoto, 2003, Proceedings. IEEE Computer Society Bioinformatics Conference.

Integrative bioinformatics analysis of transcriptional regulatory programs in breast cancer cells

Michael Q. Zhang, Andrew D. Smith, Atsushi Niida, 2008, BMC Bioinformatics.

Open source clustering software

Satoru Miyano, Seiya Imoto, J. Nolan, 2004 .

Computational Strategy for Discovering Druggable Gene Networks from Genome-Wide RNA Expression Profiles

Deborah Sanders, Satoru Miyano, Satoru Kuhara, 2005, Pacific Symposium on Biocomputing.

ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2006, Bioinform..

Transform of visual analogue scale data and their clustering

Satoru Miyano, Kenji Watanabe, Seiya Imoto, 2011, Int. J. Knowl. Eng. Soft Data Paradigms.

Partial Order-Based Bayesian Network Learning Algorithm for Estimating Gene Networks

Satoru Miyano, Seiya Imoto, Kazuyuki Numata, 2008, 2008 IEEE International Conference on Bioinformatics and Biomedicine.

Inferring dynamic gene networks under varying conditions for transcriptomic network comparison

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2010, Bioinform..

ExonMiner: Web service for analysis of GeneChip Exon array data

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2008, BMC Bioinformatics.

Principal component analysis using QR decomposition

Kuldip K. Paliwal, Satoru Miyano, Alok Sharma, 2013, Int. J. Mach. Learn. Cybern..

Symbolic hierarchical clustering for visual analogue scale data

Satoru Miyano, Kenji Watanabe, Seiya Imoto, 2011 .

Using Protein-Protein Interactions for Refining Gene Networks Estimated from Microarray Data by Bayesian Networks

Satoru Miyano, Seiya Imoto, Naoki Nariai, 2003, Pacific Symposium on Biocomputing.

A feature selection method using improved regularized linear discriminant analysis

Kuldip K. Paliwal, Satoru Miyano, Alok Sharma, 2014, Machine Vision and Applications.

WEIGHTED LASSO IN GRAPHICAL GAUSSIAN MODELING FOR LARGE GENE NETWORK ESTIMATION BASED ON MICROARRAY DATA

Satoru Miyano, Teppei Shimamura, Seiya Imoto, 2007 .

Model-free unsupervised gene set screening based on information enrichment in expression profiles

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2010, Bioinform..

Dynamic Bayesian Network and Nonparametric Regression Model for Inferring Gene Networks

Sun Yong Kim, Satoru Miyano, Seiya Imoto, 2002 .

Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2021, PLoS Comput. Biol..

On the application of BERT models for nanopore methylation detection

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Application of state-space model with skew-t measurement noise to blood test value prediction

Seiya Imoto, Rui Yamaguchi, Takanori Hasegawa, 2021 .

Analysis of Questionnaire for Traditional Medicine and Development of Decision Support System

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2014, Evidence-based complementary and alternative medicine : eCAM.

Estimating Nonlinear Regression Models based on Radial Basis Function Networks

Seiya Imoto, Tomohiro Ando, Sadanori Konishi, 2001 .

Error tolerant model for incorporating biological knowledge with expression data in estimating gene networks

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2006 .

Identifying drug active pathways from gene networks estimated by gene expression data.

Satoru Miyano, Seiya Imoto, Yoshinori Tamada, 2005, Genome informatics. International Conference on Genome Informatics.

Prediction of blood test values under different lifestyle scenarios using time-series electronic health record

Seiya Imoto, Rui Yamaguchi, Takanori Hasegawa, 2020, PloS one.

Comprehensive analysis of indels in whole-genome microsatellite regions and microsatellite instability across 21 cancer types

Satoru Miyano, Yuichi Shiraishi, Seiya Imoto, 2018, bioRxiv.

Evaluation of Sequence Features from Intrinsically Disordered Regions for the Estimation of Protein Function

Satoru Miyano, Abdollah Dehzangi, Kenta Nakai, 2014, PloS one.

A novel meta-analysis approach of cancer transcriptomes reveals prevailing transcriptional networks in cancer cells.

Masao Nagasaki, Satoru Miyano, Atsushi Niida, 2010, Genome informatics. International Conference on Genome Informatics.

Clustering samples characterized by time course gene expression profiles using the mixture of state space models.

Satoru Miyano, Tomoyuki Higuchi, Seiya Imoto, 2007, Genome informatics. International Conference on Genome Informatics.

Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets

Satoru Miyano, Seiya Imoto, Heewon Park, 2015, PloS one.

A Novel Network Profiling Analysis Reveals System Changes in Epithelial-Mesenchymal Transition

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2011, PloS one.

FUNCTIONAL DISCRIMINANT ANALYSIS FOR MICROARRAY GENE EXPRESSION DATA VIA RADIAL BASIS FUNCTION NETWORKS

Yuko Araki, Seiya Imoto, Sadanori Konishi, 2004 .

Identification of activated transcription factors from microarray gene expression data of Kampo medicine-treated mice.

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2007, Genome informatics. International Conference on Genome Informatics.

Blautia genus associated with visceral fat accumulation in adults 20–76 years of age

Seiya Imoto, Shigeyuki Nakaji, Shinichiro Saito, 2019, npj Biofilms and Microbiomes.

Metagenomic analysis of bacterial species in tongue microbiome of current and never smokers

Seiya Imoto, Rui Yamaguchi, Takanori Hasegawa, 2020, npj Biofilms and Microbiomes.

Statistical Analysis of Hie (Cold Sensation) and Hiesho (Cold Disorder) in Kampo Clinic

Satoru Miyano, Seiya Imoto, Rui Yamaguchi, 2013, Evidence-based complementary and alternative medicine : eCAM.

Analysis of gene networks for drug target discovery and validation.

Satoru Miyano, Seiya Imoto, Yoshinori Tamada, 2007, Methods in molecular biology.

Predicting differences in gene regulatory systems by state space models.

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2008, Genome informatics. International Conference on Genome Informatics.

Memory-Efficient Clustering Algorithms for Microarray Gene Expression Data

Satoru Miyano, Hideo Bannai, Seiya Imoto, 2005 .

Comprehensive phosphoproteome analysis unravels the core signaling network that initiates the earliest synapse pathology in preclinical Alzheimer's disease brain.

Satoru Miyano, Seiya Imoto, Takeshi Iwatsubo, 2015, Human molecular genetics.

A statistical framework for genome-wide discovery of biomarker splice variations with GeneChip Human Exon 1.0 ST Arrays.

Masao Nagasaki, Atsushi Doi, Satoru Miyano, 2006, Genome informatics. International Conference on Genome Informatics.

Germline determinants of the somatic mutation landscape in 2,642 cancer genomes

Gunnar Rätsch, Mark Gerstein, Li Ding, 2017, bioRxiv.

91 FADS AND FALLACIES IN THE NAME OF SMALL-SAMPLE MICROARRAY CLASSIFICATION

Rabab K. Ward, Petar M. Djuric, Sergios Theodoridis, 2007 .

Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma

Masao Nagasaki, Satoru Miyano, Teppei Shimamura, 2012, PloS one.

Selection of smoothing parameters inB-spline nonparametric regression models using information criteria

Seiya Imoto, Sadanori Konishi, S. Konishi, 2003 .

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

Masao Nagasaki, Satoru Miyano, Seiya Imoto, 2014, PloS one.

Gene Set-Based Module Discovery Decodes cis-Regulatory Codes Governing Diverse Gene Expression across Human Multiple Tissues

Masao Nagasaki, Satoru Miyano, Atsushi Niida, 2010, PloS one.

Analysis of PPARα-dependent and PPARα-independent transcript regulation following fenofibrate treatment of human endothelial cells

Masao Nagasaki, Atsushi Doi, Satoru Miyano, 2009, Angiogenesis.

Robust Prediction of Anti-Cancer Drug Sensitivity and Sensitivity-Specific Biomarker

Satoru Miyano, Teppei Shimamura, Seiya Imoto, 2014, PloS one.

Kernel mixture survival models for identifying cancer subtypes, predicting patient's cancer types and survival probabilities.

Satoru Miyano, Seiya Imoto, Tomohiro Ando, 2004, Genome informatics. International Conference on Genome Informatics.