Get started
Author

Ryo Yoshida

Observed names: R. Yoshida, RYO YOSHIDA, Yoshida, Ryo
Observed institutions: Kanazawa University, Oak Ridge National Laboratory, University of Auckland, The Graduate University for Advanced Studies, SOKENDAI, National Institute for Materials Science, University of Cambridge, Japan Science and Technology Agency, Advanced Telecommunications Research Institute International, RIKEN, The Institute of Statistical Mathematics, Research Organization of Information and Systems, Institute of Medical Science, The University of Tokyo, The University of Tokyo
ORCID: 0000-0001-8092-0162
Observed ORCID: 0000-0001-8092-0162
OpenAlex ID: A5031629643
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
2019 · Stephen Wu, Yukiko Kondo, et al. · npj Computational Materials · 491
PDF
Predicting Materials Properties with Little Data Using Shotgun Transfer Learning
2019 · Hironao Yamada, Chang Liu, et al. · ACS Central Science · 408
Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma
2012 · Mai Yamauchi, Rui Yamaguchi, et al. · PLoS ONE · 200
PDF
Bayesian molecular design with a chemical language model
2017 · Hisaki Ikebata, Kenta Hongo, et al. · Journal of Computer-Aided Molecular Design · 150
PDF
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics
2022 · Yoshihiro Hayashi, Junichiro Shiomi, et al. · npj Computational Materials · 146
PDF
Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models
2008 · Osamu Hirose, Ryo Yoshida, et al. · Bioinformatics · 93
PDF
Multitask Machine Learning to Predict Polymer–Solvent Miscibility Using Flory–Huggins Interaction Parameters
2023 · Yuta Aoki, Stephen Wu, et al. · Macromolecules · 78
PDF
Machine learning-assisted exploration of thermally conductive polymers based on high-throughput molecular dynamics simulations
2022 · Ruimin Ma, Hanfeng Zhang, et al. · Materials Today Physics · 75
Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space
2016 · Yu Toyoshima, Terumasa Tokunaga, et al. · PLoS Computational Biology · 75
PDF
Crystal structure prediction with machine learning-based element substitution
2022 · Minoru Kusaba, Chang Liu, et al. · Computational Materials Science · 68
PDF
Machine Learning to Predict Quasicrystals from Chemical Compositions
2021 · Chang Liu, Erina Fujita, et al. · Advanced Materials · 62
Neuron ID dataset facilitates neuronal annotation for whole-brain activity imaging of C. elegans
2020 · Yu Toyoshima, Stephen Wu, et al. · BMC Biology · 49
PDF
Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs
2015 · Asuka Nakata, Ryo Yoshida, et al. · Scientific Reports · 47
PDF
Automated detection and tracking of many cells by using 4D live-cell imaging data
2014 · Terumasa Tokunaga, Osamu Hirose, et al. · Bioinformatics · 46
PDF
Finding module-based gene networks with state-space models - Mining high-dimensional and short time-course gene expression data
2007 · R. Yamaguchi, R. Yoshida, et al. · IEEE Signal Processing Magazine · 46
SMiPoly: Generation of a Synthesizable Polymer Virtual Library Using Rule-Based Polymerization Reactions
2023 · Mitsuru Ohno, Yoshihiro Hayashi, et al. · Journal of Chemical Information and Modeling · 45
PDF
iQSPR in XenonPy: A Bayesian Molecular Design Algorithm
2019 · Stephen Wu, Guillaume Lambard, et al. · Molecular Informatics · 43
PDF
ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles
2006 · Ryo Yoshida, Tomoyuki Higuchi, et al. · Bioinformatics · 43
PDF
SPF-CellTracker: Tracking Multiple Cells with Strongly-Correlated Moves Using a Spatial Particle Filter
2017 · Osamu Hirose, Shotaro Kawaguchi, et al. · IEEE Transactions on Computational Biology and Bioinformatics · 41
PDF
Estimating time-dependent gene networks from time series microarray data by dynamic linear models with Markov switching
2005 · R. Yoshida, S. Imoto, et al. · IEEE Computational Systems Bioinformatics Conference (CSB) · 39
A mixed factors model for dimension reduction and extraction of a group structure in gene expression data
2004 · R. Yoshida, T. Higuchi, et al. · IEEE Computational Systems Bioinformatics Conference (CSB) · 39
Bayesian Algorithm for Retrosynthesis
2020 · Zhongliang Guo, Stephen Wu, et al. · Journal of Chemical Information and Modeling · 37
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing.
2010 · Ryo Yoshida, Mike West · PubMed · 36
SPACIER: on-demand polymer design with fully automated all-atom classical molecular dynamics integrated into machine learning pipelines
2025 · Shun Nanjo, Arifin, et al. · npj Computational Materials · 34
PDF
Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.
2006 · Masao Nagasaki, Rui Yamaguchi, et al. · PubMed · 34
Works count: 99
Citation count: 2,936
H-index: 27
I10-index: 48
Year
Topic
Type