Yoshihiro Yamanishi

Orcid: 0000-0003-2279-8773

According to our database1, Yoshihiro Yamanishi authored at least 72 papers between 2003 and 2025.

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Bibliography

2025
AI-driven transcriptome profile-guided hit molecule generation.
Artif. Intell., 2025

2024
Quantitative evaluation of molecular generation performance of graph-based GANs.
Softw. Qual. J., June, 2024

<i>De Novo</i> Generation of Chemical Structures of Inhibitor and Activator Candidates for Therapeutic Target Proteins by a Transformer-Based Variational Autoencoder and Bayesian Optimization.
J. Chem. Inf. Model., 2024

Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design.
J. Chem. Inf. Model., 2024

Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning.
J. Chem. Inf. Model., 2024

Molecular Generative Adversarial Network with Multi-Property Optimization.
CoRR, 2024

Network-based identification of diagnosis-specific trans-omic biomarkers via integration of multiple omics data.
Biosyst., 2024

TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular Generation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

GxVAEs: Two Joint VAEs Generate Hit Molecules from Gene Expression Profiles.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
EarlGAN: An enhanced actor-critic reinforcement learning agent-driven GAN for de novo drug design.
Pattern Recognit. Lett., November, 2023

SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Mode Collapse Alleviation of Reinforcement Learning-based GANs in Drug Design.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

MacGAN: A Moment-Actor-Critic Reinforcement Learning-Based Generative Adversarial Network for Molecular Generation.
Proceedings of the Web and Big Data - 7th International Joint Conference, 2023

2022
Pathway trajectory analysis with tensor imputation reveals drug-induced single-cell transcriptomic landscape.
Nat. Comput. Sci., 2022

Scaffold-Retained Structure Generator to Exhaustively Create Molecules in an Arbitrary Chemical Space.
J. Chem. Inf. Model., 2022

Epigenetic landscape of drug responses revealed through large-scale ChIP-seq data analyses.
BMC Bioinform., 2022

TRANSDIRE: data-driven direct reprogramming by a pioneer factor-guided trans-omics approach.
Bioinform., 2022

Transformer-based Objective-reinforced Generative Adversarial Network to Generate Desired Molecules.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning.
J. Chem. Inf. Model., 2021

Lean-Docking: Exploiting Ligands' Predicted Docking Scores to Accelerate Molecular Docking.
J. Chem. Inf. Model., 2021

2020
Dual graph convolutional neural network for predicting chemical networks.
BMC Bioinform., April, 2020

Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain Included.
J. Chem. Inf. Model., 2020

Space-Efficient Feature Maps for String Alignment Kernels.
Data Sci. Eng., 2020

Network-based characterization of disease-disease relationships in terms of drugs and therapeutic targets.
Bioinform., 2020

2019
Guest Editorial for the 16th Asia Pacific Bioinformatics Conference.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

A Distance-Based Boolean Applicability Domain for Classification of High Throughput Screening Data.
J. Chem. Inf. Model., 2019

Chemoinformatics and structural bioinformatics in OCaml.
J. Cheminformatics, 2019

Network-based characterization of drug-protein interaction signatures with a space-efficient approach.
BMC Syst. Biol., 2019

Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm.
Bioinform., 2019

2018
Dual Convolutional Neural Network for Graph of Graphs Link Prediction.
CoRR, 2018

Scalable Alignment Kernels via Space-Efficient Feature Maps.
CoRR, 2018

2016
Simultaneous prediction of enzyme orthologs from chemical transformation patterns for <i>de novo</i> metabolic pathway reconstruction.
Bioinform., 2016

Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015
Mining Discriminative Patterns from Graph Data with Multiple Labels and Its Application to Quantitative Structure-Activity Relationship (QSAR) Models.
J. Chem. Inf. Model., 2015

Target-Based Drug Repositioning Using Large-Scale Chemical-Protein Interactome Data.
J. Chem. Inf. Model., 2015

Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data.
J. Chem. Inf. Model., 2015

Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles.
J. Chem. Inf. Model., 2015

Metabolome-scale <i>de novo</i> pathway reconstruction using regioisomer-sensitive graph alignments.
Bioinform., 2015

2014
DINIES: drug-target interaction network inference engine based on supervised analysis.
Nucleic Acids Res., 2014

Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach.
Bioinform., 2014

2013
KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters.
Nucleic Acids Res., 2013

Scalable prediction of compound-protein interactions using minwise hashing.
BMC Syst. Biol., 2013

KCF-S: KEGG Chemical Function and Substructure for improved interpretability and prediction in chemical bioinformatics.
BMC Syst. Biol., 2013

Inferring protein domains associated with drug side effects based on drug-target interaction network.
BMC Syst. Biol., 2013

Supervised <i>de novo</i> reconstruction of metabolic pathways from metabolome-scale compound sets.
Bioinform., 2013

Succinct interval-splitting tree for scalable similarity search of compound-protein pairs with property constraints.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012
GENIES: gene network inference engine based on supervised analysis.
Nucleic Acids Res., 2012

Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces.
J. Chem. Inf. Model., 2012

Drug target prediction using adverse event report systems: a pharmacogenomic approach.
Bioinform., 2012

Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers.
Bioinform., 2012

Relating drug-protein interaction network with drug side effects.
Bioinform., 2012

2011
Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions.
J. Chem. Inf. Model., 2011

Predicting drug side-effect profiles: a chemical fragment-based approach.
BMC Bioinform., 2011

2010
Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel.
IEICE Trans. Inf. Syst., 2010

Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework.
Bioinform., 2010

2009
E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs.
Bioinform., 2009

Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach.
Bioinform., 2009

Supervised prediction of drug-target interactions using bipartite local models.
Bioinform., 2009

Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction.
Proceedings of the SIAM International Conference on Data Mining, 2009

On Pairwise Kernels: An Efficient Alternative and Generalization Analysis.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

2008
KEGG for linking genomes to life and the environment.
Nucleic Acids Res., 2008

Supervised Bipartite Graph Inference.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Prediction of drug-target interaction networks from the integration of chemical and genomic spaces.
Proceedings of the Proceedings 16th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2008

2007
Glycan classification with tree kernels.
Bioinform., 2007

Inference of Protein-Protein Interactions by Using Co-evolutionary Information.
Proceedings of the Algebraic Biology, Second International Conference, 2007

2006
Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions.
Bioinform., 2006

2005
Sensitivity analysis in functional principal component analysis.
Comput. Stat., 2005

The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships.
Bioinform., 2005

Supervised enzyme network inference from the integration of genomic data and chemical information.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

2004
Supervised Graph Inference.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Protein network inference from multiple genomic data: a supervised approach.
Proceedings of the Proceedings Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology 2004, 2004

2003
Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis.
Proceedings of the Eleventh International Conference on Intelligent Systems for Molecular Biology, June 29, 2003


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