Protein Secondary Structure Prediction Based on Stochastic-Rule Learning. - Hiroshi Mamitsuka; Kenji Yamanishi (ALT, 1992)

A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars. - Naoki Abe; Hiroshi Mamitsuka (ICML, 1994)

Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars. - Hiroshi Mamitsuka; Naoki Abe (ISMB, 1994)

Representing inter-residue dependencies in protein sequences with probabilistic networks. - Hiroshi Mamitsuka (Comput. Appl. Biosci., 1995)

alpha-Helix region prediction with stochastic rule learning. - Hiroshi Mamitsuka; Kenji Yamanishi (Comput. Appl. Biosci., 1995)

A Learning Method of Hidden Markov Models for Sequence Discrimination. - Hiroshi Mamitsuka (J. Comput. Biol., 1996)

Supervised learning of hidden Markov models for sequence discrimination. - Hiroshi Mamitsuka (RECOMB, 1997)

Predicting Protein Secondary Structure Using Stochastic Tree Grammars. - Naoki Abe; Hiroshi Mamitsuka (Mach. Learn., 1997)

Empirical Comparison of Competing Query Learning Methods. - Naoki Abe; Hiroshi Mamitsuka; Atsuyoshi Nakamura (Discovery Science, 1998)

Query Learning Strategies Using Boosting and Bagging. - Naoki Abe; Hiroshi Mamitsuka (ICML, 1998)

Efficient Mining from Large Databases by Query Learning. - Hiroshi Mamitsuka; Naoki Abe (ICML, 2000)

Efficient Data Mining by Active Learning. - Hiroshi Mamitsuka; Naoki Abe (Progress in Discovery Science, 2002)

Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases. - Hiroshi Mamitsuka (PKDD, 2002)

Empirical Evaluation of Ensemble Feature Subset Selection Methods for Learning from a High-Dimensional Database in Drug Desig. - Hiroshi Mamitsuka (BIBE, 2003)

Detecting Experimental Noises in Protein-Protein Interactions with Iterative Sampling and Model-Based Clustering. - Hiroshi Mamitsuka (BIBE, 2003)

Efficient Mining from Heterogeneous Data Sets for Predicting Protein-Protein Interactions. - Hiroshi Mamitsuka (DEXA Workshops, 2003)

Hierarchical Latent Knowledge Analysis for Co-occurrence Data. - Hiroshi Mamitsuka (ICML, 2003)

Selective Sampling with a Hierarchical Latent Variable Model. - Hiroshi Mamitsuka (IDA, 2003)

Finding the Maximum Common Subgraph of a Partial k-Tree and a Graph with a Polynomially Bounded Number of Spanning Trees. - Atsuko Yamaguchi; Hiroshi Mamitsuka (ISAAC, 2003)

Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data. - Hiroshi Mamitsuka (SDM, 2003)

Mining biologically active patterns in metabolic pathways using microarray expression profiles. - Hiroshi Mamitsuka; Yasushi Okuno; Atsuko Yamaguchi (SIGKDD Explor., 2003)

A Hierarchical Mixture of Markov Models for Finding Biologically Active Metabolic Paths Using Gene Expression and Protein Classes. - Hiroshi Mamitsuka; Yasushi Okuno (CSB, 2004)

Application of a new probabilistic model for recognizing complex patterns in glycans. - Kiyoko F. Aoki; Nobuhisa Ueda; Atsuko Yamaguchi; Minoru Kanehisa; Tatsuya Akutsu; Hiroshi Mamitsuka (ISMB/ECCB (Supplement of Bioinformatics), 2004)

A General Probabilistic Framework for Mining Labeled Ordered Trees. - Nobuhisa Ueda; Kiyoko F. Aoki; Hiroshi Mamitsuka (SDM, 2004)

Finding the maximum common subgraph of a partial k-tree and a graph with a polynomially bounded number of spanning trees. - Atsuko Yamaguchi; Kiyoko F. Aoki; Hiroshi Mamitsuka (Inf. Process. Lett., 2004)

KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains. - Kiyoko F. Aoki; Atsuko Yamaguchi; Nobuhisa Ueda; Tatsuya Akutsu; Hiroshi Mamitsuka; Susumu Goto; Minoru Kanehisa (Nucleic Acids Res., 2004)

Managing and Analyzing Carbohydrate Data. - Kiyoko F. Aoki; Nobuhisa Ueda; Atsuko Yamaguchi; Tatsuya Akutsu; Minoru Kanehisa; Hiroshi Mamitsuka (SIGMOD Rec., 2004)

A probabilistic model for mining implicit 'chemical compound-gene' relations from literature. - Shanfeng Zhu; Yasushi Okuno; Gozoh Tsujimoto; Hiroshi Mamitsuka (ECCB/JBI, 2005)

Cleaning microarray expression data using Markov random fields based on profile similarity. - Raymond Wan 001; Hiroshi Mamitsuka; Kiyoko F. Aoki (SAC, 2005)

Computational intelligence in solving bioinformatics problems. - Krzysztof J. Cios; Hiroshi Mamitsuka; Tomomasa Nagashima; Ryszard Tadeusiewicz (Artif. Intell. Medicine, 2005)

Finding the biologically optimal alignment of multiple sequences. - Hiroshi Mamitsuka (Artif. Intell. Medicine, 2005)

A score matrix to reveal the hidden links in glycans. - Kiyoko F. Aoki; Hiroshi Mamitsuka; Tatsuya Akutsu; Minoru Kanehisa (Bioinform., 2005)

Essential Latent Knowledge for Protein-Protein Interactions: Analysis by an Unsupervised Learning Approach. - Hiroshi Mamitsuka (IEEE ACM Trans. Comput. Biol. Bioinform., 2005)

A Probabilistic Model for Mining Labeled Ordered Trees: Capturing Patterns in Carbohydrate Sugar Chains. - Nobuhisa Ueda; Kiyoko F. Aoki-Kinoshita; Atsuko Yamaguchi; Tatsuya Akutsu; Hiroshi Mamitsuka (IEEE Trans. Knowl. Data Eng., 2005)

ProfilePSTMM: capturing tree-structure motifs in carbohydrate sugar chains. - Kiyoko F. Aoki-Kinoshita; Nobuhisa Ueda; Hiroshi Mamitsuka; Minoru Kanehisa (ISMB (Supplement of Bioinformatics), 2006)

A new efficient probabilistic model for mining labeled ordered trees. - Kosuke Hashimoto; Kiyoko F. Aoki-Kinoshita; Nobuhisa Ueda; Minoru Kanehisa; Hiroshi Mamitsuka (KDD, 2006)

Combining Vector-Space and Word-Based Aspect Models for Passage Retrieval. - Raymond Wan 001; Ichigaku Takigawa; Hiroshi Mamitsuka; Vo Ngoc Anh (TREC, 2006)

Applying Gaussian Distribution-Dependent Criteria to Decision Trees for High-Dimensional Microarray Data. - Raymond Wan 001; Ichigaku Takigawa; Hiroshi Mamitsuka (VDMB, 2006)

Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules. - Shanfeng Zhu; Keiko Udaka; John Sidney; Alessandro Sette; Kiyoko F. Aoki-Kinoshita; Hiroshi Mamitsuka (Bioinform., 2006)

Query-learning-based iterative feature-subset selection for learning from high-dimensional data sets. - Hiroshi Mamitsuka (Knowl. Inf. Syst., 2006)

Selecting features in microarray classification using ROC curves. - Hiroshi Mamitsuka (Pattern Recognit., 2006)

A Probabilistic Model for Clustering Text Documents with Multiple Fields. - Shanfeng Zhu; Ichigaku Takigawa; Shuqin Zhang; Hiroshi Mamitsuka (ECIR, 2007)

Annotating gene function by combining expression data with a modular gene network. - Motoki Shiga; Ichigaku Takigawa; Hiroshi Mamitsuka (ISMB/ECCB (Supplement of Bioinformatics), 2007)

A spectral clustering approach to optimally combining numericalvectors with a modular network. - Motoki Shiga; Ichigaku Takigawa; Hiroshi Mamitsuka (KDD, 2007)

Passage Retrieval with Vector Space and Query-Level Aspect Models. - Raymond Wan 001; Vo Ngoc Anh; Hiroshi Mamitsuka (TREC, 2007)

A hidden Markov model-based approach for identifying timing differences in gene expression under different experimental factors. - Takashi Yoneya; Hiroshi Mamitsuka (Bioinform., 2007)

Predicting implicit associated cancer genes from OMIM and MEDLINE by a new probabilistic model. - Shanfeng Zhu; Yasushi Okuno; Gozoh Tsujimoto; Hiroshi Mamitsuka (BMC Syst. Biol., 2007)

Active ensemble learning: Application to data mining and bioinformatics. - Hiroshi Mamitsuka; Naoki Abe (Syst. Comput. Jpn., 2007)

Mining significant tree patterns in carbohydrate sugar chains. - Kosuke Hashimoto; Ichigaku Takigawa; Motoki Shiga; Minoru Kanehisa; Hiroshi Mamitsuka (ECCB, 2008)

Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis. - Ichigaku Takigawa; Hiroshi Mamitsuka (Bioinform., 2008)

A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology. - Kosuke Hashimoto; Kiyoko F. Aoki-Kinoshita; Nobuhisa Ueda; Minoru Kanehisa; Hiroshi Mamitsuka (ACM Trans. Knowl. Discov. Data, 2008)

Efficient Probabilistic Latent Semantic Analysis through Parallelization. - Raymond Wan 001; Vo Ngoc Anh; Hiroshi Mamitsuka (AIRS, 2009)

Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data. - Mitsunori Kayano; Ichigaku Takigawa; Motoki Shiga; Koji Tsuda; Hiroshi Mamitsuka (Bioinform., 2009)

Enhancing MEDLINE document clustering by incorporating MeSH semantic similarity. - Shanfeng Zhu; Jia Zeng; Hiroshi Mamitsuka (Bioinform., 2009)

Field independent probabilistic model for clustering multi-field documents. - Shanfeng Zhu; Ichigaku Takigawa; Jia Zeng; Hiroshi Mamitsuka (Inf. Process. Manag., 2009)

HAMSTER: visualizing microarray experiments as a set of minimum spanning trees. - Raymond Wan 001; Larisa Kiseleva; Hajime Harada; Hiroshi Mamitsuka; Paul Horton (Source Code Biol. Medicine, 2009)

Algorithms for Finding a Minimum Repetition Representation of a String. - Atsuyoshi Nakamura; Tomoya Saito; Ichigaku Takigawa; Hiroshi Mamitsuka; Mineichi Kudo (SPIRE, 2010)

A markov classification model for metabolic pathways. - Timothy Hancock; Hiroshi Mamitsuka (Algorithms Mol. Biol., 2010)

Mining metabolic pathways through gene expression. - Timothy Hancock; Ichigaku Takigawa; Hiroshi Mamitsuka (Bioinform., 2010)

Boosted Optimization for Network Classification. - Timothy Hancock; Hiroshi Mamitsuka (AISTATS, 2010)

On network-based kernel methods for protein-protein interactions with applications in protein functions prediction. - Limin Li; Wai-Ki Ching; Yatming Chan; Hiroshi Mamitsuka (J. Syst. Sci. Complex., 2010)

MetaMHC: a meta approach to predict peptides binding to MHC molecules. - Xihao Hu; Wenjian Zhou; Keiko Udaka; Hiroshi Mamitsuka; Shanfeng Zhu (Nucleic Acids Res., 2010)

Kernels for Link Prediction with Latent Feature Models. - Canh Hao Nguyen; Hiroshi Mamitsuka (ECML/PKDD (2), 2011)

Efficiently mining δ-tolerance closed frequent subgraphs. - Ichigaku Takigawa; Hiroshi Mamitsuka (Mach. Learn., 2011)

A spectral approach to clustering numerical vectors as nodes in a network. - Motoki Shiga; Ichigaku Takigawa; Hiroshi Mamitsuka (Pattern Recognit., 2011)

Discriminative Graph Embedding for Label Propagation. - Canh Hao Nguyen; Hiroshi Mamitsuka (IEEE Trans. Neural Networks, 2011)

Clustering genes with expression and beyond. - Motoki Shiga; Hiroshi Mamitsuka (WIREs Data Mining Knowl. Discov., 2011)

Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools. - Lianming Zhang; Keiko Udaka; Hiroshi Mamitsuka; Shanfeng Zhu (Briefings Bioinform., 2012)

A review of statistical methods for prediction of proteolytic cleavage. - David duVerle; Hiroshi Mamitsuka (Briefings Bioinform., 2012)

Efficient semi-supervised learning on locally informative multiple graphs. - Motoki Shiga; Hiroshi Mamitsuka (Pattern Recognit., 2012)

A Variational Bayesian Framework for Clustering with Multiple Graphs. - Motoki Shiga; Hiroshi Mamitsuka (IEEE Trans. Knowl. Data Eng., 2012)

Boosted Network Classifiers for Local Feature Selection. - Timothy Hancock; Hiroshi Mamitsuka (IEEE Trans. Neural Networks Learn. Syst., 2012)

Latent Feature Kernels for Link Prediction on Sparse Graphs. - Canh Hao Nguyen; Hiroshi Mamitsuka (IEEE Trans. Neural Networks Learn. Syst., 2012)

Mining from protein-protein interactions. - Hiroshi Mamitsuka (WIREs Data Mining Knowl. Discov., 2012)

Collaborative matrix factorization with multiple similarities for predicting drug-target interactions. - Xiaodong Zheng; Hao Ding; Hiroshi Mamitsuka; Shanfeng Zhu (KDD, 2013)

Variational Bayes co-clustering with auxiliary information. - Motoki Shiga; Hiroshi Mamitsuka (MultiClust@KDD, 2013)

Manifold-based Similarity Adaptation for Label Propagation. - Masayuki Karasuyama; Hiroshi Mamitsuka (NIPS, 2013)

Fast algorithms for finding a minimum repetition representation of strings and trees. - Atsuyoshi Nakamura; Tomoya Saito; Ichigaku Takigawa; Mineichi Kudo; Hiroshi Mamitsuka (Discret. Appl. Math., 2013)

Efficient Semisupervised MEDLINE Document Clustering With MeSH-Semantic and Global-Content Constraints. - Jun Gu; Wei Feng; Jia Zeng; Hiroshi Mamitsuka; Shanfeng Zhu (IEEE Trans. Cybern., 2013)

Multiple Graph Label Propagation by Sparse Integration. - Masayuki Karasuyama; Hiroshi Mamitsuka (IEEE Trans. Neural Networks Learn. Syst., 2013)

Similarity-based machine learning methods for predicting drug-target interactions: a brief review. - Hao Ding; Ichigaku Takigawa; Hiroshi Mamitsuka; Shanfeng Zhu (Briefings Bioinform., 2014)

NetPathMiner: R/Bioconductor package for network path mining through gene expression. - Ahmed Mohamed 002; Timothy Hancock; Canh Hao Nguyen; Hiroshi Mamitsuka (Bioinform., 2014)

Detecting Differentially Coexpressed Genesfrom Labeled Expression Data: A Brief Review. - Mitsunori Kayano; Motoki Shiga; Hiroshi Mamitsuka (IEEE ACM Trans. Comput. Biol. Bioinform., 2014)

Selecting Graph Cut Solutions via Global Graph Similarity. - Canh Hao Nguyen; Nicolas Wicker; Hiroshi Mamitsuka (IEEE Trans. Neural Networks Learn. Syst., 2014)

Instance-Wise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters. - Xiaodong Zheng; Shanfeng Zhu; Junning Gao; Hiroshi Mamitsuka (IJCAI, 2015)

MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence. - Ke Liu 002; Shengwen Peng; Junqiu Wu; ChengXiang Zhai; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2015)

MeSHSim: An R/Bioconductor package for measuring semantic similarity over MeSH headings and MEDLINE documents. - Jing Zhou; Yuxuan Shui; Shengwen Peng; Xuhui Li 001; Hiroshi Mamitsuka; Shanfeng Zhu (J. Bioinform. Comput. Biol., 2015)

BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model. - Beichen Wang; Xiaodong Chen; Hiroshi Mamitsuka; Shanfeng Zhu (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

Non-Negative Matrix Factorization with Auxiliary Information on Overlapping Groups. - Motoki Shiga; Hiroshi Mamitsuka (IEEE Trans. Knowl. Data Eng., 2015)

New Resistance Distances with Global Information on Large Graphs. - Canh Hao Nguyen; Hiroshi Mamitsuka (AISTATS, 2016)

A Robust Convex Formulation for Ensemble Clustering. - Junning Gao; Makoto Yamada; Samuel Kaski; Hiroshi Mamitsuka; Shanfeng Zhu (IJCAI, 2016)

Current status and prospects of computational resources for natural product dereplication: a review. - Ahmed Mohamed 002; Canh Hao Nguyen; Hiroshi Mamitsuka (Briefings Bioinform., 2016)

NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. - Ahmed Mohamed 002; Canh Hao Nguyen; Hiroshi Mamitsuka (Bioinform., 2016)

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing. - Shengwen Peng; Ronghui You; Hongning Wang; Chengxiang Zhai; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2016)

DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank. - Qingjun Yuan; Junning Gao; Dongliang Wu; Shihua Zhang; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2016)

Mining approximate patterns with frequent locally optimal occurrences. - Atsuyoshi Nakamura; Ichigaku Takigawa; Hisashi Tosaka; Mineichi Kudo; Hiroshi Mamitsuka (Discret. Appl. Math., 2016)

Introduction to the special issue on GIW 2016. - Shuigeng Zhou; Yi-Ping Phoebe Chen; Hiroshi Mamitsuka (J. Bioinform. Comput. Biol., 2016)

Convex Factorization Machine for Toxicogenomics Prediction. - Makoto Yamada; Wenzhao Lian; Amit Goyal 001; Jianhui Chen; Kishan Wimalawarne; Suleiman A. Khan; Samuel Kaski; Hiroshi Mamitsuka; Yi Chang 001 (KDD, 2017)

Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code. - Sohiya Yotsukura; Masayuki Karasuyama; Ichigaku Takigawa; Hiroshi Mamitsuka (Briefings Bioinform., 2017)

Computational recognition for long non-coding RNA (lncRNA): Software and databases. - Sohiya Yotsukura; David duVerle; Timothy Hancock; Yayoi Natsume-Kitatani; Hiroshi Mamitsuka (Briefings Bioinform., 2017)

Adaptive edge weighting for graph-based learning algorithms. - Masayuki Karasuyama; Hiroshi Mamitsuka (Mach. Learn., 2017)

Generalized Sparse Learning of Linear Models Over the Complete Subgraph Feature Set. - Ichigaku Takigawa; Hiroshi Mamitsuka (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Factor Analysis on a Graph. - Masayuki Karasuyama; Hiroshi Mamitsuka (AISTATS, 2018)

AiProAnnotator: Low-rank Approximation with network side information for high-performance, large-scale human Protein abnormality Annotator. - Junning Gao; Shuwei Yao; Hiroshi Mamitsuka; Shanfeng Zhu (BIBM, 2018)

Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms. - Kishan Wimalawarne; Hiroshi Mamitsuka (NeurIPS, 2018)

SIMPLE: Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectra. - Dai Hai Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (Bioinform., 2018)

GOLabeler: improving sequence-based large-scale protein function prediction by learning to rank. - Ronghui You; Zihan Zhang; Yi Xiong 002; Fengzhu Sun; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2018)

AttentionXML: Extreme Multi-Label Text Classification with Multi-Label Attention Based Recurrent Neural Networks. - Ronghui You; Suyang Dai; Zihan Zhang; Hiroshi Mamitsuka; Shanfeng Zhu (CoRR, 2018)

Convex Coupled Matrix and Tensor Completion. - Kishan Wimalawarne; Makoto Yamada; Hiroshi Mamitsuka (Neural Comput., 2018)

Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data. - Makoto Yamada; Jiliang Tang; Jose Lugo-Martinez; Ermin Hodzic; Raunak Shrestha; Avishek Saha; Hua Ouyang; Dawei Yin; Hiroshi Mamitsuka; Süleyman Cenk Sahinalp; Predrag Radivojac; Filippo Menczer; et al. (IEEE Trans. Knowl. Data Eng., 2018)

Fast and Robust Multi-View Multi-Task Learning via Group Sparsity. - Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (IJCAI, 2019)

Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning. - Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (IJCAI, 2019)

AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification. - Ronghui You; Zihan Zhang; Ziye Wang; Suyang Dai; Hiroshi Mamitsuka; Shanfeng Zhu (NeurIPS, 2019)

Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches. - Dai Hai Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (Briefings Bioinform., 2019)

Modelling G×E with historical weather information improves genomic prediction in new environments. - Jussi Gillberg; Pekka Marttinen; Hiroshi Mamitsuka; Samuel Kaski (Bioinform., 2019)

ADAPTIVE: leArning DAta-dePendenT, concIse molecular VEctors for fast, accurate metabolite identification from tandem mass spectra. - Dai Hai Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (Bioinform., 2019)

NetGO: improving large-scale protein function prediction with massive network information. - Ronghui You; Shuwei Yao; Yi Xiong 002; Xiaodi Huang; Fengzhu Sun; Hiroshi Mamitsuka; Shanfeng Zhu (Nucleic Acids Res., 2019)

Editorial. - Shuigeng Zhou; Yi-Ping Phoebe Chen; Hiroshi Mamitsuka (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String. - Atsuyoshi Nakamura; Ichigaku Takigawa; Hiroshi Mamitsuka (AAAI, 2020)

Scalable Probabilistic Matrix Factorization with Graph-Based Priors. - Jonathan Strahl; Jaakko Peltonen; Hiroshi Mamitsuka; Samuel Kaski (AAAI, 2020)

FullMeSH: improving large-scale MeSH indexing with full text. - Suyang Dai; Ronghui You; Zhiyong Lu; Xiaodi Huang; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2020)

HPOLabeler: improving prediction of human protein-phenotype associations by learning to rank. - Lizhi Liu; Xiaodi Huang; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2020)

Scaled Coupled Norms and Coupled Higher-Order Tensor Completion. - Kishan Wimalawarne; Makoto Yamada; Hiroshi Mamitsuka (Neural Comput., 2020)

Drug3D-DTI: Improved Drug-target Interaction Prediction by Incorporating Spatial Information of Small Molecules. - Zhirui Liao; Xiaodi Huang; Hiroshi Mamitsuka; Shanfeng Zhu (BIBM, 2021)

XGSEA: CROSS-species gene set enrichment analysis via domain adaptation. - Menglan Cai; Canh Hao Nguyen; Hiroshi Mamitsuka; Limin Li (Briefings Bioinform., 2021)

A survey on adverse drug reaction studies: data, tasks and machine learning methods. - Duc Anh Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (Briefings Bioinform., 2021)

Machine learning approaches for drug combination therapies. - Betül Güvenç Paltun; Samuel Kaski; Hiroshi Mamitsuka (Briefings Bioinform., 2021)

Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches. - Betül Güvenç Paltun; Hiroshi Mamitsuka; Samuel Kaski (Briefings Bioinform., 2021)

HPOFiller: identifying missing protein-phenotype associations by graph convolutional network. - Lizhi Liu; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2021)

BERTMeSH: deep contextual representation learning for large-scale high-performance MeSH indexing with full text. - Ronghui You; Yuxuan Liu; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2021)

DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction. - Ronghui You; Shuwei Yao; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2021)

On Convex Clustering Solutions. - Canh Hao Nguyen; Hiroshi Mamitsuka (CoRR, 2021)

Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels. - Dai Hai Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (CoRR, 2021)

CentSmoothie: Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions. - Duc Anh Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (CoRR, 2021)

Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels. - Dai Hai Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (Mach. Learn., 2021)

Reshaped tensor nuclear norms for higher order tensor completion. - Kishan Wimalawarne; Hiroshi Mamitsuka (Mach. Learn., 2021)

Learning on Hypergraphs With Sparsity. - Canh Hao Nguyen; Hiroshi Mamitsuka (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

HPODNets: deep graph convolutional networks for predicting human protein-phenotype associations. - Lizhi Liu; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2022)

SPARSE: a sparse hypergraph neural network for learning multiple types of latent combinations to accurately predict drug-drug interactions. - Duc Anh Nguyen; Canh Hao Nguyen; Peter Petschner; Hiroshi Mamitsuka (Bioinform., 2022)

DeepMHCII: a novel binding core-aware deep interaction model for accurate MHC-II peptide binding affinity prediction. - Ronghui You; Wei Qu; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2022)

DIVERSE: Bayesian Data IntegratiVE Learning for Precise Drug ResponSE Prediction. - Betül Güvenç Paltun; Samuel Kaski; Hiroshi Mamitsuka (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning. - Xinyi Wang; Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (ECAI, 2023)

Sc2Mol: a scaffold-based two-step molecule generator with variational autoencoder and transformer. - Zhirui Liao; Lei Xie; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2023)

DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction. - Wei Qu; Ronghui You; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2023)

Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression. - Tianxiao Cao; Lu Sun 001; Canh Hao Nguyen; Hiroshi Mamitsuka (IJCAI, 2024)

GORetriever: reranking protein-description-based GO candidates by literature-driven deep information retrieval for protein function annotation. - Huiying Yan; Shaojun Wang; Hancheng Liu; Hiroshi Mamitsuka; Shanfeng Zhu (Bioinform., 2024)

Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions. - Duc Anh Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka (IEEE Trans. Neural Networks Learn. Syst., 2024)

Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference. - Dai Hai Nguyen; Tetsuya Sakurai; Hiroshi Mamitsuka (AISTATS, 2025)

Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization. - Dai Hai Nguyen; Hiroshi Mamitsuka; Atsuyoshi Nakamura (UAI, 2025)

Beyond rigid docking: deep learning approaches for fully flexible protein-ligand interactions. - John Lee; Canh Hao Nguyen; Hiroshi Mamitsuka (Briefings Bioinform., 2025)