2021

  • Liu, C., Fujita, E., Katsura, Y., Inada, Y., Ishikawa, A., Tamura, R., Kimura, K., Yoshida, R., Machine learning to predict quasicrystals from chemical compositions. Advanced Materials. (2021).
    DOI: https://doi.org/10.1002/adma.202102507

  • Ju, S., Yoshida, R., Liu, C., Wu, S., Hongo, K., Tadano, T., Shiomi, J., Exploring diamondlike lattice thermal conductivity crystals via feature-based transfer learning. Physical Review Materials. 5:053801 (2021).
    DOI: https://doi.org/10.1103/PhysRevMaterials.5.053801

  • Kusaba, M., Liu, C., Koyama, Y., Terakura, K., Yoshida, R., Recreation of the periodic table with an unsupervised machine learning algorithm. Scientific Reports. 11:4780 (2021).
    DOI: https://doi.org/10.1038/s41598-021-81850-z

  • Minami, S., Liu, S., Wu, S., Fukumizu, K., Yoshida, R., A general class of transfer learning regression without implementation cost. Proceedings of the AAAI Conference on Artificial Intelligence. 35(10):8992-8999 (2021).
    DOI: https://ojs.aaai.org/index.php/AAAI/article/view/17087

  • 2020

  • C. Liu, E. Fujita, Y. Katsura, Y. Inada, A. Ishikawa, R. Tamura, K. Kimura, R. Yoshida (2021) Machine learning to predict quasicrystals from chemical compositions, Nature Portfolio, rs-240290/v1
    [Nature Portfolio] DOI:10.21203/rs.3.rs-240290/v1

  • S. Minami, S. Liu, S. Wu, K. Fukumizu, R. Yoshida (2020) A general class of transfer learning regression without implementation cost, In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI) 2021, in press.

  • Z. Guo, S. Wu, M. Ohno, R. Yoshida (2020) Bayesian Algorithm for Retrosynthesis, Journal of Chemical Information and Modeling, 60(10):4474–4486
    [ACS Pubilcations] DOI:https://doi.org/10.1021/acs.jcim.0c00320

  • S. Minami, S. Liu, S. Wu, K. Fukumizu, R. Yoshida (2020) A general class of transfer learning regression without implementation cost, arXiv, arXiv:2006.13228.
    [arXiv]

  • Y. Toyoshima, S. Wu, M. Kanamori, H. Sato, M. S. Jang, S. Oe, Y. Murakami, T. Teramoto, C. Park, Y. Iwasaki, T. Ishihara, R. Yoshida, Y. Iino (2020) Neuron ID dataset facilitates neuronal annotation for whole-brain activity imaging of C. elegans, BMC Biology, 18(1):1-20
    [BMC Biology] DOI:https://doi.org/10.1186/s12915-020-0745-2

  • Z. Guo, S. Wu, M. Ohno, R. Yoshida (2020) A Bayesian algorithm for retrosynthesis, arXiv, arXiv:2003.03190.
    [arXiv]

  • 2019

  • M. Kusaba, C. Liu, Y. Koyama, K. Terakura, R. Yoshida (2019) Recreation of the periodic table with an unsupervised machine learning algorithm, arXiv, arXiv:1912.10708.
    [arXiv]

  • S. Wu, G. Lambard, C. Liu, H. Yamada, R. Yoshida (2019) iQSPR in XenonPy: A Bayesian molecular design algorithm, Molecular Informatics, 39(1-2):1900107.
    [Molecular Informatics] [PubMed] DOI:https://doi.org/10.1002/minf.201900107

  • S. Ju, R. Yoshida, C. Liu, K. Hongo, T. Tadano, J. Shiomi (2019) Exploring diamond-like lattice thermal conductivity crystals via feature-based transfer learning, arXiv, arXiv:1909.11234.
    [arXiv]

  • H. Yamada, C. Liu, S. Wu, Y. Koyama, S. Ju, J. Shiomi, J. Morikawa, R. Yoshida (2019) Predicting materials properties with little data using shotgun transfer learning, ACS Central Science, 5(10):1717–1730
    [ACS Central Science] DOI:https://doi.org/10.1021/acscentsci.9b00804

  • Y. Toyoshima, S. Wu, M. Kanamori, H. Sato, M.S. Jang, S. Oe, Y. Murakami, T. Teramoto, C. Park, Y. Iwasaki, T. Ishihara, R. Yoshida, Y. Iino (2019) An annotation dataset facilitates automatic annotation of whole-brain activity imaging of C. elegans, bioRxiv, 18(1), 1-20.
    [bioRxiv] DOI:https://doi.org/10.1101/698241

  • N. Takubo, F. Yura, K. Naemura, R. Yoshida, T. Tokunaga, T. Tokihiro, H. Kurihara (2019) Cohesive and anisotropic vascular endothelial cell motility driving angiogenic morphogenesis, Scientific Reports, 9:9304.
    [Scientific Reports] DOI:https://doi.org/10.1038/s41598-019-45666-2

  • S. Wu, Y. Kondo, M. Kakimoto, B. Yang, H. Yamada, I. Kuwajima, G. Lambard, K. Hongo, Y. Xu, J. Shiomi, C. Schick, J. Morikawa, R. Yoshida (2019) Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm, npj Computational Materials, 5:66.
    [npj Computational Materials] DOI:https://doi.org/10.1038/s41524-019-0203-2

  • Y. Kawamura, S. Koyama, R. Yoshida (2019) Statistical inference of the rate of RNA polymerase II elongation by total RNA sequencing, Bioinformatics, 35(11):1877–1884.
    [Bioinformatics] [PubMed] DOI:https://doi.org/10.1093/bioinformatics/bty886

  • 2018

  • H. Ikebata, K. Hongo, T. Isomura, R. Maezono, R. Yoshida (2017) Bayesian molecular design with a chemical language model, Journal of Computer-Aided Molecular Design, 31(4):379-391.
    [PubMed] [Springer] [Software]

  • 2017

  • O. Hirose, S. Kawaguchi, T. Tokunaga, Y. Toyoshima, T. Teramoto, S. Kuge, T. Ishihara, Y. Iino, R. Yoshida (2017) SPF-CellTracker: Tracking multiple cells with strongly-correlated moves using a spatial particle filter, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(6):(1822-1831).
    [IEEE Xplore]

  • 2016

  • Y. Toyoshima, T. Tokunaga, O. Hirose, M. Kanamori, T. Teramoto, MS. Jang, S. Kuge, T. Ishihara, R. Yoshida, Y. Iino (2016) Accurate automatic detection of densely distributed cell nuclei in 3D space, PLoS Computational Biology, 12(6):e1004970.
    [PubMed][PLoS Computational Biology]

  • 2015

  • A. Nakata, R. Yoshida, R. Yamaguchi, M. Yamauchi, Y. Tamada, A. Fujita, T. Shimamura, S. Imoto, T. Higuchi, M. Nomura, T. Kimura, H. Nokihara, M. Higashiyama, K. Kondoh, H. Nishihara, A. Tojo, S. Yano, S. Miyano, N. Gotoh (2015) Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs, Scientific Reports, 5:13706.
    [PubMed][Scientific Reports]

  • H. Ikebata, R. Yoshida (2015) Repulsive parallel MCMC algorithm for discovering diverse motifs from large sequence sets, Bioinformatics, 31(10):1561-1568.
    [PubMed][Bioinformatics][Software]

  • 2014

  • H. Yamashita, T. Higuchi, R. Yoshida (2014) Atom environment kernels on molecules, Journal of Chemical Information and Modeling, 54(5):1289–1300.
    [PubMed][ACS Pubilcations]

  • T. Tokunaga, O. Hirose, S. Kawaguchi, Y. Toyoshima, T. Teramoto, H. Ikebata, S. Kuge, T. Ishihara, Y. Iino, R. Yoshida (2014) Automated detection and tracking of many cells by using 4D live-cell imaging data, Bioinformatics, 30(12):i43-i51.
    [PubMed][Bioinformatics]

  • 2013

  • T. Tokunaga, R. Yoshida, Y. Iwasaki (2013) Data assimilation for reconstructing a whole neuronal system of C. Elegans - The current state and issue, Journal of The Japan Society for Simulation Technology, 3(4):287-294. (in Japanese)

  • 2012

  • M. Yamauchi, R. Yamaguchi, A. Nakata, T. Kohno, M. Nagasaki, T. Shimamura, S. Imoto, A. Saito, K. Ueno, Y. Hatanaka, R. Yoshida, T. Higuchi, M. Nomura, D. G. Beer, J. Yokota, S. Miyano, N. Gotoh (2012) Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma, PLoS One, 7(9):e43923. [PubMed][PLoS One]

  • S. Kawano, T. Shimamura, A. Niida, S. Imoto, R. Yamaguchi, M. Nagasaki, R. Yoshida, C. Print, S. Miyano (2012) Identifying gene pathways associated with cancer characteristics via sparse statistical methods, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(4):966-972. [PubMed]

  • 2011

  • Y. Tamada, R. Yamaguchi, S. Imoto, O. Hirose, R. Yoshida, M. Nagasaki, S. Miyano (2011) SiGN-SSM: open source parallel software for estimating gene networks with state space models, Bioinformatics, 27(8):1172-1173. [PubMed][Bioinformatics][Software]

  • 2010

  • S. Kawano, T. Shimamura, A. Niida, S. Imoto, R. Yamaguchi, M. Nagasaki, R. Yoshida, C. Print, S. Miyano (2010) Discovering functional gene pathways associated with cancer heterogeneity via sparse supervised learning, Proc. IEEE Bioinformatics and Biomedicine, 253-258. (BIBM2010: Refereed conference. 61 papers are accepted as regular papers from 355 submissions (acceptance rate 17.2%)) [IEEE Xplore]

  • R. Yoshida, M. Saito, H. Nagao, T. Higuchi (2010) Bayesian experts in exploring reaction kinetics of transcription circuits, Bioinformatics, 26(18):i589-595.
    [PubMed][Bioinformatics][Supplementary Information]

  • R. Yoshida, M. West (2010) Bayesian learning in sparse graphical factor models via variational mean-field annealing, Journal of Machine Learning Research, 11:1771-1798.
    [JMLR online][Software][Supporting Information]

  • K. Hayashi, M. Saito, R. Yoshida, T. Higuchi (2010) Implementation of sequential importance sampling in GPGPU, Proceedings of the 13th International Conference on Information Fusion, 1-6. [IEEE Xplore]

  • 2009

  • K. Kojima, R. Yamaguchi, S. Imoto, M. Yamauchi, M. Nagasaki, R. Yoshida, T. Shimamura, K. Ueno, T. Higuchi, N. Gotoh, S. Miyano (2009) A state space representation of VAR models with sparse learning for dynamic gene networks, Genome Informatics, 22:56-68, 227-238. [PubMed][IBSB2009 on line]

  • R. Yoshida, T. Higuchi (2009) Graphical modeling of intercellular biochemical pathways and statistical inference, Journal of the Japan Statistical Society, Bioinformatics special edition, 38(2):213-236. (in Japanese) [CiNii]

  • K. Nakamura, R. Yoshida, M. Nagasaki, S. Miyano, T. Higuchi (2009) Parameter estimation of in silico biological pathways with particle filtering towards a petascale computing, Pacific Symposium on Biocomputing, 227-238. [PubMed][PSB on line]

  • R. Yoshida, M. Nagasaki, R. Yamaguchi, S. Imoto, S. Miyano, T. Higuchi (2008) Bayesian learning of biological pathways on genomic data assimilation, Bioinformatics, 24(22):2592-2601. [PubMed][Bioinformatics][Software]

  • K. Numata, R. Yoshida, M. Nagasaki, A. Saito, S. Imoto, S. Miyano (2008) ExonMiner: Web service for analysis of GeneChip exon array data, BMC bioinformatics, 9(1):494. [PubMed][BMC Bioinformatics][Software]

  • R. Yamaguchi, S. Imoto, M. Yamauchi, M. Nagasaki, R. Yoshida, T. Shimamura, Y. Hatanaka, K. Ueno, T. Higuchi, N. Gotoh, S. Miyano (2008) Predicting differences in gene regulatory systems by state space models, Genome Informatics, 21:101-113. Finalist Best Paper Award by 19th International Conference on Genome Informatics (GIW2008)
    [PubMed]

  • O. Hirose, R. Yoshida, R. Yamaguchi, S. Imoto, T. Higuchi, S. Miyano (2008) Analyzing time course gene expression data with biological and technical replicates to estimate gene networks by state space models, Proc. 2nd Asia International Conference on Modelling & Simulation, 940-946. (AMS2008: Refereed conference)
    [IEEE Xplore]

  • O. Hirose*, R. Yoshida*, S. Imoto, R. Yamaguchi, T. Higuchi, D. Stephen Charnock-Jones, C. Print, S. Miyano (2008) Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models, Bioinformatics, 24(7):932-42. (* These authors equally contributed this work)
    [PubMed][Bioinformatics][Software]

  • R. Yoshida, K. Numata, S. Imoto, M. Nagasaki, A. Doi, K. Ueno, S. Miyano (2007) Computational genome-wide discovery of aberrant splice variations with exon expression profiles, Proc. IEEE 7th International Symposium on Bioinformatics & Bioengineering, 715-722. [Supplementary Information][IEEE Xplore]

  • O. Hirose, R. Yoshida, R. Yamaguchi, S. Imoto, T. Higuchi, S. Miyano (2007) Clustering with time course gene expression profiles and the mixture of state space models, Genome Informatics, 18:258-266. [PubMed][World Scientific]

  • R. Yamaguchi, M. Yamamoto, S. Imoto, M. Nagasaki, R. Yoshida, K. Tsuji, A. Ishige, H. Asou, K. Watanabe, S. Miyano (2007) Identification of activated transcription factors from microarray gene expression data of Kampo-medicine treated mice, Genome Informatics, 18:119-129. [PubMed][World Scientific]

  • M. Henmi, R. Yoshida, S. Eguchi (2007) Importance sampling with the estimated sampler, Biometrika, 94(4):985-991. [Biometrika]

  • P.K. Gupta*, R. Yoshida*, S. Imoto, R. Yamaguchi, S. Miyano (2007) Statistical absolute evaluation of gene ontology terms with gene expression data, Proc. 3rd International Symposium on Bioinformatics Research and Applications, Lecture Note in Bioinformatics, Springer-Verlag, 4463:146-157. (ISBRA2007: Refereed conference) (* These authors equally contributed this work) [SpringerLink]

  • R. Yamaguchi, R. Yoshida, S. Imoto, T. Higuchi, S. Miyano (2007) Finding module-based gene networks in time-course gene expression data with state space models, IEEE Signal Processing Magazine, 24(1):37-46. [IEEE Xplore]

  • S. Tasaki, M. Nagasaki, M. Oyama, H. Hata, K. Ueno, R. Yoshida, T. Higuchi, S. Sugano, S. Miyano (2006) Modeling and estimation of dynamic EGFR pathway by data assimilation approach using time series proteomic data, Genome Informatics, 17(2):226-238. [PubMed][JSBI]

  • R. Yoshida*, K. Numata*, S. Imoto, M. Nagasaki, A. Doi, K. Ueno, S. Miyano (2006) A statistical framework for genome-wide discovery of biomarker splice variations with GeneChip Human Exon 1.0 ST arrays, Genome Informatics, 17(1):88-99. (* These authors equally contributed this work) [PubMed][JSBI][Supplementary Information]

  • M. Nagasaki, R. Yamaguchi, R. Yoshida, S. Imoto, A. Doi, Y. Tamada, H. Matsuno, S. Miyano, T. Higuchi (2006) Genomic data assimilation for estimating Hybrid Functional Petri Net from time-course gene expression data, Genome Informatics, 17(1):46-61. [PubMed][JSBI]

  • R. Yoshida, T. Higuchi, S. Imoto, S. Miyano (2006) ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles, Bioinformatics, 22(12):1538-1539. [PubMed][Bioinformatics][Software]

  • R. Yoshida, T. Higuchi, S. Imoto (2005) Estimating time-dependent gene networks from time series DNA microarray data by dynamic linear model with Markov switching, Proc. IEEE 4th Computational Systems Bioinformatics (CSB2005: Refereed Conference), 289-298. [PubMed][CSB2005]

  • R. Yoshida, S. Imoto, T. Higuchi (2005) A penalized likelihood estimation on transcriptional module-based clustering, Proc. 1st International Workshop on Data Mining and Bioinformatics (DMBIO 2005: Refereed Conference), Lecture Note in Computer Science, 3482, Springer-Verlag, 389-401. [SpringerLink]

  • R. Yoshida (2004) Method for approximating target distribution of Importance Sampling, Journal of the Statistical Society Japanese Issue, 34:21-37.

  • R. Yoshida, T. Higuchi, S. Imoto (2004) A mixed factors model for dimension reduction and extraction of a group structure in gene expression data, Proc. IEEE 3rd Computational Systems Bioinformatics (CSB2004: Refereed Conference), 161-172. [PubMed][CSB2004]
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