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ORCIDYasushi Okuno
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Journal Articles
- 2024
[j43]Gert-Jan Bekker
, Kanji Oshima, Mitsugu Araki, Yasushi Okuno, Narutoshi Kamiya:
Binding Mechanism between Platelet Glycoprotein and Cyclic Peptide Elucidated by McMD-Based Dynamic Docking. J. Chem. Inf. Model. 64(10): 4158-4167 (2024)- 2023
- [j42]Narumi Hatano, Mayumi Kamada, Ryosuke Kojima, Yasushi Okuno:
Network-based prediction approach for cancer-specific driver missense mutations using a graph neural network. BMC Bioinform. 24(1): 383 (2023) - [j41]Tomoaki Mimoto, Hiroyuki Yokoyama, Toru Nakamura, Takamasa Isohara, Masayuki Hashimoto, Ryosuke Kojima, Aki Hasegawa, Yasushi Okuno:
Privacy-Preserving Correlation Coefficient. IEICE Trans. Inf. Syst. 106(5): 868-876 (2023) - [j40]Kazuki Nakamura, Eiichiro Uchino, Noriaki Sato, Ayano Araki, Kei Terayama, Ryosuke Kojima, Koichi Murashita, Ken Itoh, Tatsuya Mikami, Yoshinori Tamada, Yasushi Okuno:
Individual health-disease phase diagrams for disease prevention based on machine learning. J. Biomed. Informatics 144: 104448 (2023) - [j39]Takuto Koyama, Shigeyuki Matsumoto, Hiroaki Iwata, Ryosuke Kojima, Yasushi Okuno:
Improving Compound-Protein Interaction Prediction by Self-Training with Augmenting Negative Samples. J. Chem. Inf. Model. 63(15): 4552-4559 (2023) - [j38]Hiroaki Iwata, Taichi Nakai, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima, Yasushi Okuno:
VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search. J. Chem. Inf. Model. 63(23): 7392-7400 (2023) - 2022
- [j37]Noriaki Sato, Yoshinori Tamada, Guangchuang Yu, Yasushi Okuno:
CBNplot: Bayesian network plots for enrichment analysis. Bioinform. 38(10): 2959-2960 (2022) - [j36]Takumi Washio, Xiaoke Cui, Ryo Kanada, Jun-ichi Okada, Seiryo Sugiura, Yasushi Okuno, Shoji Takada, Toshiaki Hisada:
Using incomplete Cholesky factorization to increase the time step in molecular dynamics simulations. J. Comput. Appl. Math. 415: 114519 (2022) - [j35]Kenichiro Takaba, Chiduru Watanabe, Atsushi Tokuhisa, Yoshinobu Akinaga, Biao Ma, Ryo Kanada, Mitsugu Araki, Yasushi Okuno, Yusuke Kawashima, Hirotomo Moriwaki, Norihito Kawashita, Teruki Honma, Kaori Fukuzawa, Shigenori Tanaka:
Protein-ligand binding affinity prediction of cyclin-dependent kinase-2 inhibitors by dynamically averaged fragment molecular orbital-based interaction energy. J. Comput. Chem. 43(20): 1362-1371 (2022) - [j34]Shoichi Ishida, Kei Terayama, Ryosuke Kojima, Kiyosei Takasu, Yasushi Okuno:
AI-Driven Synthetic Route Design Incorporated with Retrosynthesis Knowledge. J. Chem. Inf. Model. 62(6): 1357-1367 (2022) - [j33]Atsushi Tokuhisa, Yoshinobu Akinaga, Kei Terayama, Yuji Okamoto, Yasushi Okuno:
Single-Image Super-Resolution Improvement of X-ray Single-Particle Diffraction Images Using a Convolutional Neural Network. J. Chem. Inf. Model. 62(14): 3352-3364 (2022) - 2021
- [j32]Noriaki Sato, Eiichiro Uchino, Ryosuke Kojima, Shusuke Hiragi, Motoko Yanagita, Yasushi Okuno:
Prediction and visualization of acute kidney injury in intensive care unit using one-dimensional convolutional neural networks based on routinely collected data. Comput. Methods Programs Biomed. 206: 106129 (2021) - [j31]Biao Ma, Kei Terayama, Shigeyuki Matsumoto, Yuta Isaka, Yoko Sasakura, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno:
Structure-Based de Novo Molecular Generator Combined with Artificial Intelligence and Docking Simulations. J. Chem. Inf. Model. 61(7): 3304-3313 (2021) - [j30]Gert-Jan Bekker, Mitsugu Araki, Kanji Oshima, Yasushi Okuno, Narutoshi Kamiya:
Accurate Binding Configuration Prediction of a G-Protein-Coupled Receptor to Its Antagonist Using Multicanonical Molecular Dynamics-Based Dynamic Docking. J. Chem. Inf. Model. 61(10): 5161-5171 (2021) - [j29]Shuntaro Chiba, Kenji Rowel Q. Lim, Narin Sheri, Saeed Anwar, Esra Erkut, Md Nur Ahad Shah, Tejal Aslesh, Stanley Woo, Omar Sheikh, Rika Maruyama, Hiroaki Takano, Katsuhiko Kunitake, William Duddy, Yasushi Okuno, Yoshitsugu Aoki, Toshifumi Yokota:
eSkip-Finder: a machine learning-based web application and database to identify the optimal sequences of antisense oligonucleotides for exon skipping. Nucleic Acids Res. 49(Webserver-Issue): 193-198 (2021) - [j28]Shigeyuki Matsumoto, Shoichi Ishida, Mitsugu Araki, Takayuki Kato, Kei Terayama, Yasushi Okuno:
Extraction of protein dynamics information from cryo-EM maps using deep learning. Nat. Mach. Intell. 3(2): 153-160 (2021) - 2020
- [j27]Hiroshi Koshimizu, Ryosuke Kojima, Kazuomi Kario, Yasushi Okuno:
Prediction of blood pressure variability using deep neural networks. Int. J. Medical Informatics 136: 104067 (2020) - [j26]Eiichiro Uchino, Kanata Suzuki, Noriaki Sato, Ryosuke Kojima, Yoshinori Tamada, Shusuke Hiragi, Hideki Yokoi, Nobuhiro Yugami, Sachiko Minamiguchi, Hironori Haga, Motoko Yanagita, Yasushi Okuno:
Classification of glomerular pathological findings using deep learning and nephrologist-AI collective intelligence approach. Int. J. Medical Informatics 141: 104231 (2020) - [j25]Gert-Jan Bekker, Mitsugu Araki, Kanji Oshima, Yasushi Okuno, Narutoshi Kamiya:
Exhaustive search of the configurational space of heat-shock protein 90 with its inhibitor by multicanonical molecular dynamics based dynamic docking. J. Comput. Chem. 41(17): 1606-1615 (2020) - [j24]Ryosuke Kojima, Shoichi Ishida, Masateru Ohta, Hiroaki Iwata, Teruki Honma, Yasushi Okuno:
kGCN: a graph-based deep learning framework for chemical structures. J. Cheminformatics 12(1): 32 (2020) - [j23]Ryosuke Shibukawa, Shoichi Ishida, Kazuki Yoshizoe, Kunihiro Wasa, Kiyosei Takasu, Yasushi Okuno, Kei Terayama, Koji Tsuda:
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration. J. Cheminformatics 12(1): 52 (2020) - [j22]Atsushi Tokuhisa, Ryo Kanada, Shuntaro Chiba, Kei Terayama, Yuta Isaka, Biao Ma, Narutoshi Kamiya, Yasushi Okuno:
Coarse-Grained Diffraction Template Matching Model to Retrieve Multiconformational Models for Biomolecule Structures from Noisy Diffraction Patterns. J. Chem. Inf. Model. 60(6): 2803-2818 (2020) - [j21]Koichiro Kato, Tomohide Masuda, Chiduru Watanabe, Naoki Miyagawa, Hideo Mizouchi, Shumpei Nagase, Kikuko Kamisaka, Kanji Oshima, Satoshi Ono, Hiroshi Ueda, Atsushi Tokuhisa, Ryo Kanada, Masateru Ohta, Mitsunori Ikeguchi, Yasushi Okuno, Kaori Fukuzawa, Teruki Honma:
High-Precision Atomic Charge Prediction for Protein Systems Using Fragment Molecular Orbital Calculation and Machine Learning. J. Chem. Inf. Model. 60(7): 3361-3368 (2020) - 2019
- [j20]Shuntaro Chiba, Yasushi Okuno, Teruki Honma, Mitsunori Ikeguchi:
Force-field parametrization based on radial and energy distribution functions. J. Comput. Chem. 40(29): 2577-2585 (2019) - [j19]Shoichi Ishida, Kei Terayama, Ryosuke Kojima, Kiyosei Takasu, Yasushi Okuno:
Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional Networks. J. Chem. Inf. Model. 59(12): 5026-5033 (2019) - 2018
- [j18]Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda:
Machine learning accelerates MD-based binding pose prediction between ligands and proteins. Bioinform. 34(5): 770-778 (2018) - [j17]Mitsugu Araki, Hiroaki Iwata, Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno:
Improving the Accuracy of Protein-Ligand Binding Mode Prediction Using a Molecular Dynamics-Based Pocket Generation Approach. J. Comput. Chem. 39(32): 2679-2689 (2018) - 2016
- [j16]Mitsugu Araki, Narutoshi Kamiya, Miwa Sato, Masahiko Nakatsui, Takatsugu Hirokawa, Yasushi Okuno:
The Effect of Conformational Flexibility on Binding Free Energy Estimation between Kinases and Their Inhibitors. J. Chem. Inf. Model. 56(12): 2445-2456 (2016) - 2014
- [j15]J. B. Brown, Yasushi Okuno, Gilles Marcou, Alexandre Varnek, Dragos Horvath:
Computational chemogenomics: Is it more than inductive transfer? J. Comput. Aided Mol. Des. 28(6): 597-618 (2014) - 2013
- [j14]Shinnosuke Seki, Yasushi Okuno:
On the Behavior of Tile Assembly System at High Temperatures. Comput. 2(2): 107-124 (2013) - [j13]Akira Shiraishi, Satoshi Niijima, J. B. Brown, Masahiko Nakatsui, Yasushi Okuno:
Chemical Genomics Approach for GPCR-Ligand Interaction Prediction and Extraction of Ligand Binding Determinants. J. Chem. Inf. Model. 53(6): 1253-1262 (2013) - [j12]Szilárd Zsolt Fazekas, Hiro Ito, Yasushi Okuno, Shinnosuke Seki, Kei Taneishi:
On computational complexity of graph inference from counting. Nat. Comput. 12(4): 589-603 (2013) - 2012
- [j11]Satoshi Niijima, Akira Shiraishi, Yasushi Okuno:
Dissecting Kinase Profiling Data to Predict Activity and Understand Cross-Reactivity of Kinase Inhibitors. J. Chem. Inf. Model. 52(4): 901-912 (2012) - 2011
- [j10]Satoshi Niijima, Hiroaki Yabuuchi, Yasushi Okuno:
Cross-Target View to Feature Selection: Identification of Molecular Interaction Features in Ligand-Target Space. J. Chem. Inf. Model. 51(1): 15-24 (2011) - 2010
- [j9]Eelke van der Horst, Julio E. Peironcely, Adriaan P. IJzerman, Margot W. Beukers, Jonathan Robert Lane, Herman W. T. van Vlijmen, Michael T. M. Emmerich, Yasushi Okuno, Andreas Bender:
A novel chemogenomics analysis of G protein-coupled receptors (GPCRs) and their ligands: a potential strategy for receptor de-orphanization. BMC Bioinform. 11: 316 (2010) - 2009
- [j8]Eelke van der Horst, Yasushi Okuno, Andreas Bender, Adriaan P. IJzerman:
Substructure Mining of GPCR Ligands Reveals Activity-Class Specific Functional Groups in an Unbiased Manner. J. Chem. Inf. Model. 49(2): 348-360 (2009) - [j7]Satoshi Niijima, Yasushi Okuno:
Laplacian Linear Discriminant Analysis Approach to Unsupervised Feature Selection. IEEE ACM Trans. Comput. Biol. Bioinform. 6(4): 605-614 (2009) - 2008
- [j6]Yasushi Okuno, Akiko Tamon, Hiroaki Yabuuchi, Satoshi Niijima, Yohsuke Minowa, Koichiro Tonomura, Ryo Kunimoto, Chunlai Feng:
GLIDA: GPCR - ligand database for chemical genomics drug discovery - database and tools update. Nucleic Acids Res. 36(Database-Issue): 907-912 (2008) - 2007
- [j5]Shanfeng Zhu, Yasushi Okuno, Gozoh Tsujimoto, Hiroshi Mamitsuka:
Predicting implicit associated cancer genes from OMIM and MEDLINE by a new probabilistic model. BMC Syst. Biol. 1(S-1): P16 (2007) - 2006
- [j4]Yasushi Okuno, Jiyoon Yang, Kei Taneishi, Hiroaki Yabuuchi, Gozoh Tsujimoto:
GLIDA: GPCR-ligand database for chemical genomic drug discovery. Nucleic Acids Res. 34(Database-Issue): 673-677 (2006) - 2004
- [j3]Minoru Kanehisa, Susumu Goto, Shuichi Kawashima, Yasushi Okuno, Masahiro Hattori:
The KEGG resource for deciphering the genome. Nucleic Acids Res. 32(Database-Issue): 277-280 (2004) - 2003
- [j2]Hiroshi Mamitsuka, Yasushi Okuno, Atsuko Yamaguchi:
Mining biologically active patterns in metabolic pathways using microarray expression profiles. SIGKDD Explor. 5(2): 113-121 (2003) - 2002
- [j1]Susumu Goto, Yasushi Okuno, Masahiro Hattori, Takaaki Nishioka, Minoru Kanehisa:
LIGAND: database of chemical compounds and reactions in biological pathways. Nucleic Acids Res. 30(1): 402-404 (2002)
Conference and Workshop Papers
- 2023
- [c8]Kimihiro Yamazaki, Yuichiro Wada, Atsushi Tokuhisa, Mutsuyo Wada, Takashi Katoh, Yuhei Umeda, Yasushi Okuno, Akira Nakagawa:
An Auto-Encoder to Reconstruct Structure with Cryo-EM Images via Theoretically Guaranteed Isometric Latent Space, and Its Application for Automatically Computing the Conformational Pathway. MICCAI (1) 2023: 394-404 - 2022
- [c7]Tomoaki Mimoto, Masayuki Hashimoto, Hiroyuki Yokoyama, Toru Nakamura, Takamasa Isohara, Ryosuke Kojima, Aki Hasegawa, Yasushi Okuno:
Differential Privacy under Incalculable Sensitivity. CSP 2022: 27-31 - 2019
- [c6]Mayumi Kamada, Toshiaki Katayama, Shuichi Kawashima, Ryosuke Kojima, Masahiko Nakatsui, Yasushi Okuno:
Med2RDF: Semantic Biomedical Knowledge-base and APIs for the Clinical Genome Medicine. SWAT4HCLS 2019: 161-162 - 2017
- [c5]Mayumi Kamada, Toshiaki Katayama, Shuichi Kawashima, Ryosuke Kojima, Masahiko Nakatsui, Yasushi Okuno:
Construction of Knowledge-Base for Clinical Interpretation of Genomic Variants. SWAT4LS 2017 - 2012
- [c4]J. B. Brown, Satoshi Niijima, Akira Shiraishi, Masahiko Nakatsui, Yasushi Okuno:
Chemogenomic approach to comprehensive predictions of ligand-target interactions: A comparative study. BIBM Workshops 2012: 136-142 - [c3]Shinnosuke Seki, Yasushi Okuno:
On the Behavior of Tile Assembly System at High Temperatures. CiE 2012: 549-559 - 2005
- [c2]Shanfeng Zhu, Yasushi Okuno, Gozoh Tsujimoto, Hiroshi Mamitsuka:
A probabilistic model for mining implicit 'chemical compound-gene' relations from literature. ECCB/JBI 2005: 251 - 2004
- [c1]Hiroshi Mamitsuka, Yasushi Okuno:
A Hierarchical Mixture of Markov Models for Finding Biologically Active Metabolic Paths Using Gene Expression and Protein Classes. CSB 2004: 341-352
Informal and Other Publications
- 2024
- [i8]Taisei Tosaki, Eiichiro Uchino, Ryosuke Kojima, Yohei Mineharu, Mikio Arita, Nobuyuki Miyai, Yoshinori Tamada, Tatsuya Mikami, Koichi Murashita, Shigeyuki Nakaji, Yasushi Okuno:
Out-of-distribution Reject Option Method for Dataset Shift Problem in Early Disease Onset Prediction. CoRR abs/2405.19864 (2024) - 2023
- [i7]Kazuma Inoue, Ryosuke Kojima, Mayumi Kamada, Yasushi Okuno:
An end-to-end framework for gene expression classification by integrating a background knowledge graph: application to cancer prognosis prediction. CoRR abs/2306.17202 (2023) - [i6]Aya Nakamura, Ryosuke Kojima, Yuji Okamoto, Eiichiro Uchino, Yohei Mineharu, Yohei Harada, Mayumi Kamada, Manabu Muto, Motoko Yanagita, Yasushi Okuno:
A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data. CoRR abs/2307.11487 (2023) - 2022
- [i5]Kazuki Nakamura, Eiichiro Uchino, Noriaki Sato, Ayano Araki, Kei Terayama, Ryosuke Kojima, Koichi Murashita, Ken Itoh, Tatsuya Mikami, Yoshinori Tamada, Yasushi Okuno:
Individual health-disease phase diagrams for disease prevention based on machine learning. CoRR abs/2205.15598 (2022) - [i4]Atsuko Takagi, Mayumi Kamada, Eri Hamatani, Ryosuke Kojima, Yasushi Okuno:
GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network. CoRR abs/2212.10788 (2022) - 2021
- [i3]Yoshihisa Tanaka, Ryosuke Kojima, Shoichi Ishida, Fumiyoshi Yamashita, Yasushi Okuno:
Complex network prediction using deep learning. CoRR abs/2104.03871 (2021) - 2020
- [i2]Kazuki Nakamura, Ryosuke Kojima, Eiichiro Uchino, Koichi Murashita, Ken Itoh, Shigeyuki Nakaji, Yasushi Okuno:
Health improvement framework for planning actionable treatment process using surrogate Bayesian model. CoRR abs/2010.16087 (2020) - 2012
- [i1]Shinnosuke Seki, Yasushi Okuno:
On the behavior of tile assembly system at high temperatures. CoRR abs/1211.4949 (2012)
Coauthor Index
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last updated on 2024-08-05 21:24 CEST by the dblp team
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