| Representation learning applications in biological sequence analysis H Iuchi, T Matsutani, K Yamada, N Iwano, S Sumi, S Hosoda, S Zhao, ... Computational and Structural Biotechnology Journal 19, 3198-3208, 2021 | 71 | 2021 |
| Discovering novel mutation signatures by latent Dirichlet allocation with variational Bayes inference T Matsutani, Y Ueno, T Fukunaga, M Hamada Bioinformatics 35 (22), 4543-4552, 2019 | 15 | 2019 |
| Parallelized latent dirichlet allocation provides a novel interpretability of mutation signatures in cancer genomes T Matsutani, M Hamada Genes 11 (10), 1127, 2020 | 5 | 2020 |
| Identification of RNA biomarkers for chemical safety screening in neural cells derived from mouse embryonic stem cells using RNA deep sequencing analysis H Tani, T Matsutani, H Aoki, K Nakamura, Y Hamaguchi, T Nakazato, ... Biochemical and biophysical research communications 512 (4), 641-646, 2019 | 3 | 2019 |
| Clone decomposition based on mutation signatures provides novel insights into mutational processes T Matsutani, M Hamada NAR genomics and bioinformatics 3 (4), lqab093, 2021 | 2 | 2021 |
| A new method to assign SNPs to mutation signatures considering heterogeneity and the application on blood cancer T Matsutani, M Hamada CANCER SCIENCE 113, 1792-1792, 2022 | | 2022 |
| トピックモデルを用いたがんゲノムの変異シグネチャー解析 T MATSUTANI, Y UENO, T FUKUNAGATSU, M HAMADA 電子情報通信学会技術研究報告 117 (109 (NC2017 5-19)), 159-164, 2017 | | 2017 |
