| Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm S Wu, Y Kondo, M Kakimoto, B Yang, H Yamada, I Kuwajima, G Lambard, ... Npj Computational Materials 5 (1), 66, 2019 | 302 | 2019 |
| Predicting materials properties with little data using shotgun transfer learning H Yamada, C Liu, S Wu, Y Koyama, S Ju, J Shiomi, J Morikawa, ... ACS central science 5 (10), 1717-1730, 2019 | 298 | 2019 |
| Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma M Yamauchi, R Yamaguchi, A Nakata, T Kohno, M Nagasaki, ... Public Library of Science 7 (9), e43923, 2012 | 155 | 2012 |
| Bayesian molecular design with a chemical language model H Ikebata, K Hongo, T Isomura, R Maezono, R Yoshida Journal of computer-aided molecular design 31, 379-391, 2017 | 139 | 2017 |
| Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models O Hirose, R Yoshida, S Imoto, R Yamaguchi, T Higuchi, ... Bioinformatics 24 (7), 932-942, 2008 | 113 | 2008 |
| Bayesian learning in sparse graphical factor models via variational mean-field annealing R Yoshida, M West The Journal of Machine Learning Research 11, 1771-1798, 2010 | 70 | 2010 |
| Finding module-based gene networks with state-space models-Mining high-dimensional and short time-course gene expression data R Yamaguchi, R Yoshida, S Imoto, T Higuchi, S Miyano IEEE Signal processing magazine 24 (1), 37-46, 2007 | 62 | 2007 |
| Accurate automatic detection of densely distributed cell nuclei in 3D space Y Toyoshima, T Tokunaga, O Hirose, M Kanamori, T Teramoto, MS Jang, ... PLoS computational biology 12 (6), e1004970, 2016 | 59 | 2016 |
| Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data M Nagasaki, R Yamaguchi, R Yoshida, S Imoto, A Doi, Y Tamada, ... Genome Informatics 17 (1), 46-61, 2006 | 53 | 2006 |
| Exploring diamondlike lattice thermal conductivity crystals via feature-based transfer learning S Ju, R Yoshida, C Liu, S Wu, K Hongo, T Tadano, J Shiomi Physical Review Materials 5 (5), 053801, 2021 | 49 | 2021 |
| Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs A Nakata, R Yoshida, R Yamaguchi, M Yamauchi, Y Tamada, A Fujita, ... Scientific reports 5 (1), 13076, 2015 | 47 | 2015 |
| A mixed factors model for dimension reduction and extraction of a group structure in gene expression data R Yoshida, T Higuchi, S Imoto Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004 …, 2004 | 47 | 2004 |
| PARAMETER ESTIMATION OF IN SILICO BIOLOGICAL PATHWAYS WITH PARTICLE FILTERING TOWARDS A PETASCALE COMPUTING K Nakamura, R Yoshida, M Nagasaki, S Miyano, T Higuchi Biocomputing 2009, 227-238, 2009 | 46 | 2009 |
| Machine learning to predict quasicrystals from chemical compositions C Liu, E Fujita, Y Katsura, Y Inada, A Ishikawa, R Tamura, K Kimura, ... Advanced Materials 33 (36), 2102507, 2021 | 41 | 2021 |
| Modeling and estimation of dynamic EGFR pathway by data assimilation approach using time series proteomic data S Tasaki, M Nagasaki, M Oyama, H Hata, K Ueno, R Yoshida, T Higuchi, ... Genome Informatics 17 (2), 226-238, 2006 | 40 | 2006 |
| ArrayCluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles R Yoshida, T Higuchi, S Imoto, S Miyano Bioinformatics 22 (12), 1538-1539, 2006 | 39 | 2006 |
| Importance sampling via the estimated sampler M Henmi, R Yoshida, S Eguchi Biometrika 94 (4), 985-991, 2007 | 37 | 2007 |
| A state space representation of VAR models with sparse learning for dynamic gene networks K Kojima, R Yamaguchi, S Imoto, M Yamauchi, M Nagasaki, R Yoshida, ... Genome Informatics 2009: Genome Informatics Series Vol. 22, 56-68, 2010 | 36 | 2010 |
| Bayesian algorithm for retrosynthesis Z Guo, S Wu, M Ohno, R Yoshida Journal of Chemical Information and Modeling 60 (10), 4474-4486, 2020 | 34 | 2020 |
| iQSPR in xenonpy: a bayesian molecular design algorithm S Wu, G Lambard, C Liu, H Yamada, R Yoshida Molecular informatics 39 (1-2), 1900107, 2020 | 30 | 2020 |
Seiya ImotoProfessor of Institute of Medical Science, University of TokyoVerified email at ims.u-tokyo.ac.jp
