| 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 | 387 | 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 | 352 | 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 | 169 | 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 | 158 | 2017 |
| データ同化入門: 次世代のシミュレーション技術 樋口， 知之， 上野， 玄太， 中野， 中村， 和幸， 吉田 (No Title), 2011 | 137 | 2011 |
| 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 | 116 | 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 | 76 | 2010 |
| 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 | 67 | 2021 |
| RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics Y Hayashi, J Shiomi, J Morikawa, R Yoshida npj Computational Materials 8 (1), 222, 2022 | 64 | 2022 |
| 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 | 63 | 2016 |
| 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 | 63 | 2007 |
| 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 | 59 | 2021 |
| 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 |
| 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 | 51 | 2015 |
| 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 | 51 | 2009 |
| 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 | 49 | 2004 |
| Crystal structure prediction with machine learning-based element substitution M Kusaba, C Liu, R Yoshida Computational Materials Science 211, 111496, 2022 | 48 | 2022 |
| Machine learning-assisted exploration of thermally conductive polymers based on high-throughput molecular dynamics simulations R Ma, H Zhang, J Xu, L Sun, Y Hayashi, R Yoshida, J Shiomi, J Wang, ... Materials Today Physics 28, 100850, 2022 | 44 | 2022 |
| 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 | 44 | 2006 |
| Neuron ID dataset facilitates neuronal annotation for whole-brain activity imaging of C. elegans Y Toyoshima, S Wu, M Kanamori, H Sato, MS Jang, S Oe, Y Murakami, ... BMC biology 18, 1-20, 2020 | 42 | 2020 |
Seiya ImotoProfessor of Institute of Medical Science, University of TokyoPatvirtintas el. paštas ims.u-tokyo.ac.jp