Hiroshi Mamitsuka
Orcid: 0000-0002-6607-5617Affiliations:
- Kyoto University, Bioinformatics Center, Japan
According to our database1,
Hiroshi Mamitsuka
authored at least 145 papers
between 1992 and 2024.
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Bibliography
2024
IEEE Trans. Neural Networks Learn. Syst., August, 2024
Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
2023
DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction.
Bioinform., September, 2023
Sc2Mol: a scaffold-based two-step molecule generator with variational autoencoder and transformer.
Bioinform., January, 2023
Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference.
CoRR, 2023
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023
2022
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
HPODNets: deep graph convolutional networks for predicting human protein-phenotype associations.
Bioinform., 2022
2021
Mach. Learn., 2021
CentSmoothie: Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions.
CoRR, 2021
CoRR, 2021
DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction.
Bioinform., 2021
BERTMeSH: deep contextual representation learning for large-scale high-performance MeSH indexing with full text.
Bioinform., 2021
HPOFiller: identifying missing protein-phenotype associations by graph convolutional network.
Bioinform., 2021
Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches.
Briefings Bioinform., 2021
Briefings Bioinform., 2021
Briefings Bioinform., 2021
Briefings Bioinform., 2021
Drug3D-DTI: Improved Drug-target Interaction Prediction by Incorporating Spatial Information of Small Molecules.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
Neural Comput., 2020
HPOLabeler: improving prediction of human protein-phenotype associations by learning to rank.
Bioinform., 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
NetGO: improving large-scale protein function prediction with massive network information.
Nucleic Acids Res., 2019
ADAPTIVE: leArning DAta-dePendenT, concIse molecular VEctors for fast, accurate metabolite identification from tandem mass spectra.
Bioinform., 2019
Modelling G×E with historical weather information improves genomic prediction in new environments.
Bioinform., 2019
Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches.
Briefings Bioinform., 2019
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
2018
IEEE Trans. Knowl. Data Eng., 2018
AttentionXML: Extreme Multi-Label Text Classification with Multi-Label Attention Based Recurrent Neural Networks.
CoRR, 2018
GOLabeler: improving sequence-based large-scale protein function prediction by learning to rank.
Bioinform., 2018
SIMPLE: Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectra.
Bioinform., 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
AiProAnnotator: Low-rank Approximation with network side information for high-performance, large-scale human Protein abnormality Annotator.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
IEEE Trans. Pattern Anal. Mach. Intell., 2017
Briefings Bioinform., 2017
Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code.
Briefings Bioinform., 2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
2016
Discret. Appl. Math., 2016
DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank.
Bioinform., 2016
Bioinform., 2016
NMRPro: an integrated web component for interactive processing and visualization of NMR spectra.
Bioinform., 2016
Current status and prospects of computational resources for natural product dereplication: a review.
Briefings Bioinform., 2016
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
IEEE Trans. Knowl. Data Eng., 2015
BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model.
IEEE ACM Trans. Comput. Biol. Bioinform., 2015
MeSHSim: An R/Bioconductor package for measuring semantic similarity over MeSH headings and MEDLINE documents.
J. Bioinform. Comput. Biol., 2015
MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence.
Bioinform., 2015
Instance-Wise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
2014
IEEE Trans. Neural Networks Learn. Syst., 2014
Detecting Differentially Coexpressed Genesfrom Labeled Expression Data: A Brief Review.
IEEE ACM Trans. Comput. Biol. Bioinform., 2014
NetPathMiner: R/Bioconductor package for network path mining through gene expression.
Bioinform., 2014
Similarity-based machine learning methods for predicting drug-target interactions: a brief review.
Briefings Bioinform., 2014
2013
IEEE Trans. Neural Networks Learn. Syst., 2013
Efficient Semisupervised MEDLINE Document Clustering With MeSH-Semantic and Global-Content Constraints.
IEEE Trans. Cybern., 2013
Fast algorithms for finding a minimum repetition representation of strings and trees.
Discret. Appl. Math., 2013
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 5-8, 2013
Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, 2013
Collaborative matrix factorization with multiple similarities for predicting drug-target interactions.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013
2012
IEEE Trans. Neural Networks Learn. Syst., 2012
IEEE Trans. Neural Networks Learn. Syst., 2012
IEEE Trans. Knowl. Data Eng., 2012
Pattern Recognit., 2012
Briefings Bioinform., 2012
Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools.
Briefings Bioinform., 2012
2011
IEEE Trans. Neural Networks, 2011
Pattern Recognit., 2011
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011
2010
Nucleic Acids Res., 2010
On network-based kernel methods for protein-protein interactions with applications in protein functions prediction.
J. Syst. Sci. Complex., 2010
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Proceedings of the String Processing and Information Retrieval, 2010
2009
Source Code Biol. Medicine, 2009
Inf. Process. Manag., 2009
Bioinform., 2009
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data.
Bioinform., 2009
Proceedings of the Information Retrieval Technology, 2009
2008
A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology.
ACM Trans. Knowl. Discov. Data, 2008
Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis.
Bioinform., 2008
Proceedings of the ECCB'08 Proceedings, 2008
2007
Syst. Comput. Jpn., 2007
Predicting implicit associated cancer genes from OMIM and MEDLINE by a new probabilistic model.
BMC Syst. Biol., 2007
A hidden Markov model-based approach for identifying timing differences in gene expression under different experimental factors.
Bioinform., 2007
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
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007
Proceedings of the Advances in Information Retrieval, 2007
2006
Pattern Recognit., 2006
Query-learning-based iterative feature-subset selection for learning from high-dimensional data sets.
Knowl. Inf. Syst., 2006
Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules.
Bioinform., 2006
Applying Gaussian Distribution-Dependent Criteria to Decision Trees for High-Dimensional Microarray Data.
Proceedings of the Data Mining and Bioinformatics, First International Workshop, 2006
Proceedings of the Fifteenth Text REtrieval Conference, 2006
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006
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 Protein-Protein Interactions: Analysis by an Unsupervised Learning Approach.
IEEE ACM Trans. Comput. Biol. Bioinform., 2005
Artif. Intell. Medicine, 2005
Artif. Intell. 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 compound-gene' 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
KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains.
Nucleic Acids Res., 2004
Finding the maximum common subgraph of a partial <i>k</i>-tree and a graph with a polynomially bounded number of spanning trees.
Inf. Process. Lett., 2004
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 Explor., 2003
Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data.
Proceedings of the Third SIAM International Conference on Data Mining, 2003
Finding the Maximum Common Subgraph of a Partial k-Tree and a Graph with a Polynomially Bounded Number of Spanning Trees.
Proceedings of the Algorithms and Computation, 14th International Symposium, 2003
Proceedings of the Advances in Intelligent Data Analysis V, 2003
Proceedings of the Machine Learning, 2003
Efficient Mining from Heterogeneous Data Sets for Predicting Protein-Protein Interactions.
Proceedings of the 14th International Workshop on Database and Expert Systems Applications (DEXA'03), 2003
Detecting Experimental Noises in Protein-Protein Interactions with Iterative Sampling and Model-Based 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 High-Dimensional Database in Drug Desig.
Proceedings of the 3rd IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2003), 2003
2002
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002
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
Proceedings of the Discovery Science, 1998
1997
Mach. Learn., 1997
Proceedings of the First Annual International Conference on Research in Computational Molecular Biology, 1997
1996
J. Comput. Biol., 1996
1995
Comput. Appl. Biosci., 1995
Representing inter-residue dependencies in protein sequences with probabilistic networks.
Comput. Appl. Biosci., 1995
1994
Predicting Location and Structure Of beta-Sheet 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
Proceedings of the Algorithmic Learning Theory, Third Workshop, 1992