Hiroshi Mamitsuka

ORCID

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 63

Top Venues

Bioinform.

Briefings Bioinform.

CoRR

IEEE ACM Trans. Comput. Biol. Bioinform.

Publications

Duc Anh Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions. IEEE Trans. Neural Networks Learn. Syst. 35 (8) (2024)
Xinyi Wang, Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka
Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning. ECAI (2023)
Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka
Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference. CoRR (2023)
Zhirui Liao, Lei Xie, Hiroshi Mamitsuka, Shanfeng Zhu
Sc2Mol: a scaffold-based two-step molecule generator with variational autoencoder and transformer. Bioinform. 39 (1) (2023)
Wei Qu, Ronghui You, Hiroshi Mamitsuka, Shanfeng Zhu
DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction. Bioinform. 39 (9) (2023)
Lizhi Liu, Hiroshi Mamitsuka, Shanfeng Zhu
HPODNets: deep graph convolutional networks for predicting human protein-phenotype associations. Bioinform. 38 (3) (2022)
Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka
DIVERSE: Bayesian Data IntegratiVE Learning for Precise Drug ResponSE Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (4) (2022)
Zhirui Liao, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu
Drug3D-DTI: Improved Drug-target Interaction Prediction by Incorporating Spatial Information of Small Molecules. BIBM (2021)
Kishan Wimalawarne, Hiroshi Mamitsuka
Reshaped tensor nuclear norms for higher order tensor completion. Mach. Learn. 110 (3) (2021)
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels. Mach. Learn. 110 (7) (2021)
Betül Güvenç Paltun, Hiroshi Mamitsuka, Samuel Kaski
Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches. Briefings Bioinform. 22 (1) (2021)
Duc Anh Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
A survey on adverse drug reaction studies: data, tasks and machine learning methods. Briefings Bioinform. 22 (1) (2021)
Duc Anh Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
CentSmoothie: Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions. CoRR (2021)
Ronghui You, Shuwei Yao, Hiroshi Mamitsuka, Shanfeng Zhu
DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction. Bioinform. 37 (Supplement) (2021)
Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka
Machine learning approaches for drug combination therapies. Briefings Bioinform. 22 (6) (2021)
Ronghui You, Yuxuan Liu, Hiroshi Mamitsuka, Shanfeng Zhu
BERTMeSH: deep contextual representation learning for large-scale high-performance MeSH indexing with full text. Bioinform. 37 (5) (2021)
Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka
DIVERSE: bayesian Data IntegratiVE learning for precise drug ResponSE prediction. CoRR (2021)
Canh Hao Nguyen, Hiroshi Mamitsuka
Learning on Hypergraphs With Sparsity. IEEE Trans. Pattern Anal. Mach. Intell. 43 (8) (2021)
Menglan Cai, Canh Hao Nguyen, Hiroshi Mamitsuka, Limin Li
XGSEA: CROSS-species gene set enrichment analysis via domain adaptation. Briefings Bioinform. 22 (5) (2021)
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels. CoRR (2021)
Canh Hao Nguyen, Hiroshi Mamitsuka
On Convex Clustering Solutions. CoRR (2021)
Lizhi Liu, Hiroshi Mamitsuka, Shanfeng Zhu
HPOFiller: identifying missing protein-phenotype associations by graph convolutional network. Bioinform. 37 (19) (2021)
Lizhi Liu, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu
HPOLabeler: improving prediction of human protein-phenotype associations by learning to rank. Bioinform. 36 (14) (2020)
Suyang Dai, Ronghui You, Zhiyong Lu, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu
FullMeSH: improving large-scale MeSH indexing with full text. Bioinform. 36 (5) (2020)
Atsuyoshi Nakamura, Ichigaku Takigawa, Hiroshi Mamitsuka
Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String. AAAI (2020)
Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka
Scaled Coupled Norms and Coupled Higher-Order Tensor Completion. Neural Comput. 32 (2) (2020)
Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski
Scalable Probabilistic Matrix Factorization with Graph-Based Priors. AAAI (2020)
Ronghui You, Shuwei Yao, Yi Xiong, Xiaodi Huang, Fengzhu Sun, Hiroshi Mamitsuka, Shanfeng Zhu
NetGO: improving large-scale protein function prediction with massive network information. Nucleic Acids Res. 47 (Webserver-Issue) (2019)
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches. Briefings Bioinform. 20 (6) (2019)
Jussi Gillberg, Pekka Marttinen, Hiroshi Mamitsuka, Samuel Kaski
Modelling G×E with historical weather information improves genomic prediction in new environments. Bioinform. 35 (20) (2019)
Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski
Scalable Probabilistic Matrix Factorization with Graph-Based Priors. CoRR (2019)
Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka
Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning. IJCAI (2019)
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
ADAPTIVE: leArning DAta-dePendenT, concIse molecular VEctors for fast, accurate metabolite identification from tandem mass spectra. Bioinform. 35 (14) (2019)
Shuigeng Zhou, Yi-Ping Phoebe Chen, Hiroshi Mamitsuka
Editorial. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (2) (2019)
Ronghui You, Zihan Zhang, Ziye Wang, Suyang Dai, Hiroshi Mamitsuka, Shanfeng Zhu
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification. NeurIPS (2019)
Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka
Fast and Robust Multi-View Multi-Task Learning via Group Sparsity. IJCAI (2019)
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, Yi Chang
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data. IEEE Trans. Knowl. Data Eng. 30 (7) (2018)
Ronghui You, Zihan Zhang, Yi Xiong, Fengzhu Sun, Hiroshi Mamitsuka, Shanfeng Zhu
GOLabeler: improving sequence-based large-scale protein function prediction by learning to rank. Bioinform. 34 (14) (2018)
Kishan Wimalawarne, Hiroshi Mamitsuka
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms. NeurIPS (2018)
Masayuki Karasuyama, Hiroshi Mamitsuka
Factor Analysis on a Graph. AISTATS (2018)
Junning Gao, Shuwei Yao, Hiroshi Mamitsuka, Shanfeng Zhu
AiProAnnotator: Low-rank Approximation with network side information for high-performance, large-scale human Protein abnormality Annotator. BIBM (2018)
Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka
Convex Coupled Matrix and Tensor Completion. Neural Comput. 30 (11) (2018)
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
SIMPLE: Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectra. Bioinform. 34 (13) (2018)
Ronghui You, Suyang Dai, Zihan Zhang, Hiroshi Mamitsuka, Shanfeng Zhu
AttentionXML: Extreme Multi-Label Text Classification with Multi-Label Attention Based Recurrent Neural Networks. CoRR (2018)
Canh Hao Nguyen, Hiroshi Mamitsuka
Learning on Hypergraphs with Sparsity. CoRR (2018)
Sohiya Yotsukura, Masayuki Karasuyama, Ichigaku Takigawa, Hiroshi Mamitsuka
Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code. Briefings Bioinform. 18 (4) (2017)
Ichigaku Takigawa, Hiroshi Mamitsuka
Generalized Sparse Learning of Linear Models Over the Complete Subgraph Feature Set. IEEE Trans. Pattern Anal. Mach. Intell. 39 (3) (2017)
Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A. Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang
Convex Factorization Machine for Toxicogenomics Prediction. KDD (2017)
Masayuki Karasuyama, Hiroshi Mamitsuka
Adaptive edge weighting for graph-based learning algorithms. Mach. Learn. 106 (2) (2017)
Sohiya Yotsukura, David duVerle, Timothy Hancock, Yayoi Natsume-Kitatani, Hiroshi Mamitsuka
Computational recognition for long non-coding RNA (lncRNA): Software and databases. Briefings Bioinform. 18 (1) (2017)
Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu
A Robust Convex Formulation for Ensemble Clustering. IJCAI (2016)
Qingjun Yuan, Junning Gao, Dongliang Wu, Shihua Zhang, Hiroshi Mamitsuka, Shanfeng Zhu
DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank. Bioinform. 32 (12) (2016)
Ahmed Mohamed, Canh Hao Nguyen, Hiroshi Mamitsuka
NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinform. 32 (13) (2016)
Shengwen Peng, Ronghui You, Hongning Wang, Chengxiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu
DeepMeSH: deep semantic representation for improving large-scale MeSH indexing. Bioinform. 32 (12) (2016)
Ahmed Mohamed, Canh Hao Nguyen, Hiroshi Mamitsuka
Current status and prospects of computational resources for natural product dereplication: a review. Briefings Bioinform. 17 (2) (2016)
Atsuyoshi Nakamura, Ichigaku Takigawa, Hisashi Tosaka, Mineichi Kudo, Hiroshi Mamitsuka
Mining approximate patterns with frequent locally optimal occurrences. Discret. Appl. Math. 200 (2016)
Shuigeng Zhou, Yi-Ping Phoebe Chen, Hiroshi Mamitsuka
Introduction to the special issue on GIW 2016. J. Bioinform. Comput. Biol. 14 (5) (2016)
Canh Hao Nguyen, Hiroshi Mamitsuka
New Resistance Distances with Global Information on Large Graphs. AISTATS (2016)
Ke Liu, Shengwen Peng, Junqiu Wu, ChengXiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu
MeSHLabeler: improving the accuracy of large-scale MeSH indexing by integrating diverse evidence. Bioinform. 31 (12) (2015)
Xiaodong Zheng, Shanfeng Zhu, Junning Gao, Hiroshi Mamitsuka
Instance-Wise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters. IJCAI (2015)
Jing Zhou, Yuxuan Shui, Shengwen Peng, Xuhui Li, Hiroshi Mamitsuka, Shanfeng Zhu
MeSHSim: An R/Bioconductor package for measuring semantic similarity over MeSH headings and MEDLINE documents. J. Bioinform. Comput. Biol. 13 (6) (2015)
Beichen Wang, Xiaodong Chen, Hiroshi Mamitsuka, Shanfeng Zhu
BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model. IEEE ACM Trans. Comput. Biol. Bioinform. 12 (6) (2015)
Motoki Shiga, Hiroshi Mamitsuka
Non-Negative Matrix Factorization with Auxiliary Information on Overlapping Groups. IEEE Trans. Knowl. Data Eng. 27 (6) (2015)
Mitsunori Kayano, Motoki Shiga, Hiroshi Mamitsuka
Detecting Differentially Coexpressed Genesfrom Labeled Expression Data: A Brief Review. IEEE ACM Trans. Comput. Biol. Bioinform. 11 (1) (2014)
Ahmed Mohamed, Timothy Hancock, Canh Hao Nguyen, Hiroshi Mamitsuka
NetPathMiner: R/Bioconductor package for network path mining through gene expression. Bioinform. 30 (21) (2014)
Canh Hao Nguyen, Nicolas Wicker, Hiroshi Mamitsuka
Selecting Graph Cut Solutions via Global Graph Similarity. IEEE Trans. Neural Networks Learn. Syst. 25 (7) (2014)
Hao Ding, Ichigaku Takigawa, Hiroshi Mamitsuka, Shanfeng Zhu
Similarity-based machine learning methods for predicting drug-target interactions: a brief review. Briefings Bioinform. 15 (5) (2014)
Motoki Shiga, Hiroshi Mamitsuka
Variational Bayes co-clustering with auxiliary information. MultiClust@KDD (2013)
Jun Gu, Wei Feng, Jia Zeng, Hiroshi Mamitsuka, Shanfeng Zhu
Efficient Semisupervised MEDLINE Document Clustering With MeSH-Semantic and Global-Content Constraints. IEEE Trans. Cybern. 43 (4) (2013)
Masayuki Karasuyama, Hiroshi Mamitsuka
Multiple Graph Label Propagation by Sparse Integration. IEEE Trans. Neural Networks Learn. Syst. 24 (12) (2013)
Xiaodong Zheng, Hao Ding, Hiroshi Mamitsuka, Shanfeng Zhu
Collaborative matrix factorization with multiple similarities for predicting drug-target interactions. KDD (2013)
Masayuki Karasuyama, Hiroshi Mamitsuka
Manifold-based Similarity Adaptation for Label Propagation. NIPS (2013)
Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Mineichi Kudo, Hiroshi Mamitsuka
Fast algorithms for finding a minimum repetition representation of strings and trees. Discret. Appl. Math. 161 (10-11) (2013)
Hiroshi Mamitsuka
Mining from protein-protein interactions. WIREs Data Mining Knowl. Discov. 2 (5) (2012)
David duVerle, Hiroshi Mamitsuka
A review of statistical methods for prediction of proteolytic cleavage. Briefings Bioinform. 13 (3) (2012)
Lianming Zhang, Keiko Udaka, Hiroshi Mamitsuka, Shanfeng Zhu
Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools. Briefings Bioinform. 13 (3) (2012)
Motoki Shiga, Hiroshi Mamitsuka
Efficient semi-supervised learning on locally informative multiple graphs. Pattern Recognit. 45 (3) (2012)
Canh Hao Nguyen, Hiroshi Mamitsuka
Latent Feature Kernels for Link Prediction on Sparse Graphs. IEEE Trans. Neural Networks Learn. Syst. 23 (11) (2012)
Timothy Hancock, Hiroshi Mamitsuka
Boosted Network Classifiers for Local Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 23 (11) (2012)
Motoki Shiga, Hiroshi Mamitsuka
A Variational Bayesian Framework for Clustering with Multiple Graphs. IEEE Trans. Knowl. Data Eng. 24 (4) (2012)
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
A spectral approach to clustering numerical vectors as nodes in a network. Pattern Recognit. 44 (2) (2011)
Motoki Shiga, Hiroshi Mamitsuka
Clustering genes with expression and beyond. WIREs Data Mining Knowl. Discov. 1 (6) (2011)
Canh Hao Nguyen, Hiroshi Mamitsuka
Kernels for Link Prediction with Latent Feature Models. ECML/PKDD (2) (2011)
Ichigaku Takigawa, Hiroshi Mamitsuka
-tolerance closed frequent subgraphs. Mach. Learn. 82 (2) (2011)
Canh Hao Nguyen, Hiroshi Mamitsuka
Discriminative Graph Embedding for Label Propagation. IEEE Trans. Neural Networks 22 (9) (2011)
Xihao Hu, Wenjian Zhou, Keiko Udaka, Hiroshi Mamitsuka, Shanfeng Zhu
MetaMHC: a meta approach to predict peptides binding to MHC molecules. Nucleic Acids Res. 38 (Web-Server-Issue) (2010)
Timothy Hancock, Hiroshi Mamitsuka
Boosted Optimization for Network Classification. AISTATS (2010)
Limin Li, Wai-Ki Ching, Yatming Chan, Hiroshi Mamitsuka
On network-based kernel methods for protein-protein interactions with applications in protein functions prediction. J. Syst. Sci. Complex. 23 (5) (2010)
Timothy Hancock, Ichigaku Takigawa, Hiroshi Mamitsuka
Mining metabolic pathways through gene expression. Bioinform. 26 (17) (2010)
Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Hiroshi Mamitsuka, Mineichi Kudo
Algorithms for Finding a Minimum Repetition Representation of a String. SPIRE (2010)
Timothy Hancock, Hiroshi Mamitsuka
A markov classification model for metabolic pathways. Algorithms Mol. Biol. 5 (2010)
Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data. Bioinform. 25 (21) (2009)
Raymond Wan, Vo Ngoc Anh, Hiroshi Mamitsuka
Efficient Probabilistic Latent Semantic Analysis through Parallelization. AIRS (2009)
Shanfeng Zhu, Jia Zeng, Hiroshi Mamitsuka
Enhancing MEDLINE document clustering by incorporating MeSH semantic similarity. Bioinform. 25 (15) (2009)
Timothy Hancock, Hiroshi Mamitsuka
A Markov Classification Model for Metabolic Pathways. WABI (2009)
Shanfeng Zhu, Ichigaku Takigawa, Jia Zeng, Hiroshi Mamitsuka
Field independent probabilistic model for clustering multi-field documents. Inf. Process. Manag. 45 (5) (2009)
Raymond Wan, Larisa Kiseleva, Hajime Harada, Hiroshi Mamitsuka, Paul Horton
HAMSTER: visualizing microarray experiments as a set of minimum spanning trees. Source Code Biol. Medicine 4 (2009)
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka
A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology. ACM Trans. Knowl. Discov. Data 2 (1) (2008)
Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka
Mining significant tree patterns in carbohydrate sugar chains. ECCB (2008)
Ichigaku Takigawa, Hiroshi Mamitsuka
Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis. Bioinform. 24 (2) (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hiroshi Mamitsuka