Hiroshi Mamitsuka
According to our database^{1}, Hiroshi Mamitsuka
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Bibliography
2018
Factor Analysis on a Graph.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Generalized Sparse Learning of Linear Models Over the Complete Subgraph Feature Set.
IEEE Trans. Pattern Anal. Mach. Intell., 2017
Adaptive edge weighting for graphbased learning algorithms.
Machine Learning, 2017
Computational recognition for long noncoding RNA (lncRNA): Software and databases.
Briefings in Bioinformatics, 2017
Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code.
Briefings in Bioinformatics, 2017
Convex Factorization Machine for Toxicogenomics Prediction.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
2016
Introduction to the special issue on GIW 2016.
J. Bioinformatics and Computational Biology, 2016
Mining approximate patterns with frequent locally optimal occurrences.
Discrete Applied Mathematics, 2016
DrugERank: improving drugtarget interaction prediction of new candidate drugs or targets by ensemble learning to rank.
Bioinformatics, 2016
DeepMeSH: deep semantic representation for improving largescale MeSH indexing.
Bioinformatics, 2016
NMRPro: an integrated web component for interactive processing and visualization of NMR spectra.
Bioinformatics, 2016
Current status and prospects of computational resources for natural product dereplication: a review.
Briefings in Bioinformatics, 2016
A Robust Convex Formulation for Ensemble Clustering.
Proceedings of the TwentyFifth International Joint Conference on Artificial Intelligence, 2016
New Resistance Distances with Global Information on Large Graphs.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
NonNegative Matrix Factorization with Auxiliary Information on Overlapping Groups.
IEEE Trans. Knowl. Data Eng., 2015
BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model.
IEEE/ACM Trans. Comput. Biology Bioinform., 2015
MeSHSim: An R/Bioconductor package for measuring semantic similarity over MeSH headings and MEDLINE documents.
J. Bioinformatics and Computational Biology, 2015
MeSHLabeler: improving the accuracy of largescale MeSH indexing by integrating diverse evidence.
Bioinformatics, 2015
InstanceWise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters.
Proceedings of the TwentyFourth International Joint Conference on Artificial Intelligence, 2015
2014
Selecting Graph Cut Solutions via Global Graph Similarity.
IEEE Trans. Neural Netw. Learning Syst., 2014
Detecting Differentially Coexpressed Genesfrom Labeled Expression Data: A Brief Review.
IEEE/ACM Trans. Comput. Biology Bioinform., 2014
NetPathMiner: R/Bioconductor package for network path mining through gene expression.
Bioinformatics, 2014
Similaritybased machine learning methods for predicting drugtarget interactions: a brief review.
Briefings in Bioinformatics, 2014
2013
Multiple Graph Label Propagation by Sparse Integration.
IEEE Trans. Neural Netw. Learning Syst., 2013
Efficient Semisupervised MEDLINE Document Clustering With MeSHSemantic and GlobalContent Constraints.
IEEE Trans. Cybernetics, 2013
Fast algorithms for finding a minimum repetition representation of strings and trees.
Discrete Applied Mathematics, 2013
Manifoldbased Similarity Adaptation for Label Propagation.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 58, 2013
Variational Bayes coclustering with auxiliary information.
Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, 2013
Collaborative matrix factorization with multiple similarities for predicting drugtarget interactions.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013
2012
Mining from proteinprotein interactions.
Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery, 2012
Latent Feature Kernels for Link Prediction on Sparse Graphs.
IEEE Trans. Neural Netw. Learning Syst., 2012
Boosted Network Classifiers for Local Feature Selection.
IEEE Trans. Neural Netw. Learning Syst., 2012
A Variational Bayesian Framework for Clustering with Multiple Graphs.
IEEE Trans. Knowl. Data Eng., 2012
Efficient semisupervised learning on locally informative multiple graphs.
Pattern Recognition, 2012
A review of statistical methods for prediction of proteolytic cleavage.
Briefings in Bioinformatics, 2012
Toward more accurate panspecific MHCpeptide binding prediction: a review of current methods and tools.
Briefings in Bioinformatics, 2012
2011
Clustering genes with expression and beyond.
Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery, 2011
Discriminative Graph Embedding for Label Propagation.
IEEE Trans. Neural Networks, 2011
A spectral approach to clustering numerical vectors as nodes in a network.
Pattern Recognition, 2011
Efficiently mining δtolerance closed frequent subgraphs.
Machine Learning, 2011
Kernels for Link Prediction with Latent Feature Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011
2010
MetaMHC: a meta approach to predict peptides binding to MHC molecules.
Nucleic Acids Research, 2010
On networkbased kernel methods for proteinprotein interactions with applications in protein functions prediction.
J. Systems Science & Complexity, 2010
Boosted Optimization for Network Classification.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Mining metabolic pathways through gene expression.
Bioinformatics, 2010
A markov classification model for metabolic pathways.
Algorithms for Molecular Biology, 2010
Algorithms for Finding a Minimum Repetition Representation of a String.
Proceedings of the String Processing and Information Retrieval, 2010
2009
HAMSTER: visualizing microarray experiments as a set of minimum spanning trees.
Source Code for Biology and Medicine, 2009
Field independent probabilistic model for clustering multifield documents.
Inf. Process. Manage., 2009
Enhancing MEDLINE document clustering by incorporating MeSH semantic similarity.
Bioinformatics, 2009
Efficiently finding genomewide threeway gene interactions from transcript and genotypedata.
Bioinformatics, 2009
A Markov Classification Model for Metabolic Pathways.
Proceedings of the Algorithms in Bioinformatics, 9th International Workshop, 2009
Efficient Probabilistic Latent Semantic Analysis through Parallelization.
Proceedings of the Information Retrieval Technology, 2009
2008
A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology.
TKDD, 2008
Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis.
Bioinformatics, 2008
Mining significant tree patterns in carbohydrate sugar chains.
Proceedings of the ECCB'08 Proceedings, 2008
2007
Active ensemble learning: Application to data mining and bioinformatics.
Systems and Computers in Japan, 2007
Predicting implicit associated cancer genes from OMIM and MEDLINE by a new probabilistic model.
BMC Systems Biology, 2007
A hidden Markov modelbased approach for identifying timing differences in gene expression under different experimental factors.
Bioinformatics, 2007
Passage Retrieval with Vector Space and QueryLevel Aspect Models.
Proceedings of The Sixteenth Text REtrieval Conference, 2007
A spectral clustering approach to optimally combining numericalvectors with a modular network.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007
Annotating gene function by combining expression data with a modular gene network.
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007
A Probabilistic Model for Clustering Text Documents with Multiple Fields.
Proceedings of the Advances in Information Retrieval, 2007
2006
Selecting features in microarray classification using ROC curves.
Pattern Recognition, 2006
Querylearningbased iterative featuresubset selection for learning from highdimensional data sets.
Knowl. Inf. Syst., 2006
Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules.
Bioinformatics, 2006
Applying Gaussian DistributionDependent Criteria to Decision Trees for HighDimensional Microarray Data.
Proceedings of the Data Mining and Bioinformatics, First International Workshop, 2006
Combining VectorSpace and WordBased Aspect Models for Passage Retrieval.
Proceedings of the Fifteenth Text REtrieval Conference, 2006
A new efficient probabilistic model for mining labeled ordered trees.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006
ProfilePSTMM: capturing treestructure motifs in carbohydrate sugar chains.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006
2005
A Probabilistic Model for Mining Labeled Ordered Trees: Capturing Patterns in Carbohydrate Sugar Chains.
IEEE Trans. Knowl. Data Eng., 2005
Essential Latent Knowledge for ProteinProtein Interactions: Analysis by an Unsupervised Learning Approach.
IEEE/ACM Trans. Comput. Biology Bioinform., 2005
A score matrix to reveal the hidden links in glycans.
Bioinformatics, 2005
Finding the biologically optimal alignment of multiple sequences.
Artificial Intelligence in Medicine, 2005
Computational intelligence in solving bioinformatics problems.
Artificial Intelligence in Medicine, 2005
Cleaning microarray expression data using Markov random fields based on profile similarity.
Proceedings of the 2005 ACM Symposium on Applied Computing (SAC), 2005
A probabilistic model for mining implicit 'chemical compoundgene' relations from literature.
Proceedings of the ECCB/JBI'05 Proceedings, Fourth European Conference on Computational Biology/Sixth Meeting of the Spanish Bioinformatics Network (Jornadas de BioInformática), Palacio de Congresos, Madrid, Spain, September 28, 2005
2004
Managing and Analyzing Carbohydrate Data.
SIGMOD Record, 2004
KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains.
Nucleic Acids Research, 2004
Finding the maximum common subgraph of a partial ktree and a graph with a polynomially bounded number of spanning trees.
Inf. Process. Lett., 2004
A General Probabilistic Framework for Mining Labeled Ordered Trees.
Proceedings of the Fourth SIAM International Conference on Data Mining, 2004
Application of a new probabilistic model for recognizing complex patterns in glycans.
Proceedings of the Proceedings Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology 2004, 2004
A Hierarchical Mixture of Markov Models for Finding Biologically Active Metabolic Paths Using Gene Expression and Protein Classes.
Proceedings of the 3rd International IEEE Computer Society Computational Systems Bioinformatics Conference, 2004
2003
Mining biologically active patterns in metabolic pathways using microarray expression profiles.
SIGKDD Explorations, 2003
Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Cooccurrence Data.
Proceedings of the Third SIAM International Conference on Data Mining, 2003
Finding the Maximum Common Subgraph of a Partial kTree and a Graph with a Polynomially Bounded Number of Spanning Trees.
Proceedings of the Algorithms and Computation, 14th International Symposium, 2003
Selective Sampling with a Hierarchical Latent Variable Model.
Proceedings of the Advances in Intelligent Data Analysis V, 2003
Hierarchical Latent Knowledge Analysis for Cooccurrence Data.
Proceedings of the Machine Learning, 2003
Efficient Mining from Heterogeneous Data Sets for Predicting ProteinProtein Interactions.
Proceedings of the 14th International Workshop on Database and Expert Systems Applications (DEXA'03), 2003
Detecting Experimental Noises in ProteinProtein Interactions with Iterative Sampling and ModelBased Clustering.
Proceedings of the 3rd IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2003), 2003
Empirical Evaluation of Ensemble Feature Subset Selection Methods for Learning from a HighDimensional Database in Drug Desig.
Proceedings of the 3rd IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2003), 2003
2002
Iteratively Selecting Feature Subsets for Mining from HighDimensional Databases.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002
Efficient Data Mining by Active Learning.
Proceedings of the Progress in Discovery Science, 2002
2000
Efficient Mining from Large Databases by Query Learning.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000
1998
Query Learning Strategies Using Boosting and Bagging.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998
Empirical Comparison of Competing Query Learning Methods.
Proceedings of the Discovery Science, 1998
1997
Predicting Protein Secondary Structure Using Stochastic Tree Grammars.
Machine Learning, 1997
Supervised learning of hidden Markov models for sequence discrimination.
Proceedings of the First Annual International Conference on Research in Computational Molecular Biology, 1997
1996
A Learning Method of Hidden Markov Models for Sequence Discrimination.
Journal of Computational Biology, 1996
1995
alphaHelix region prediction with stochastic rule learning.
Computer Applications in the Biosciences, 1995
Representing interresidue dependencies in protein sequences with probabilistic networks.
Computer Applications in the Biosciences, 1995
1994
Predicting Location and Structure Of betaSheet Regions Using Stochastic Tree Grammars.
Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, 1994
A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars.
Proceedings of the Machine Learning, 1994
1992
Protein Secondary Structure Prediction Based on StochasticRule Learning.
Proceedings of the Algorithmic Learning Theory, Third Workshop, 1992