| Multi-step regression learning for compositional distributional semantics E Grefenstette, G Dinu, YZ Zhang, M Sadrzadeh, M Baroni arXiv preprint arXiv:1301.6939, 2013 | 154 | 2013 |
| A novel ASXL1–OGT axis plays roles in H3K4 methylation and tumor suppression in myeloid malignancies D Inoue, T Fujino, P Sheridan, Y Zhang, R Nagase, S Horikawa, Z Li, ... Leukemia 32 (6), 1327-1337, 2018 | 67 | 2018 |
| Functional restoration of bacteriomes and viromes by fecal microbiota transplantation K Fujimoto, Y Kimura, JR Allegretti, M Yamamoto, Y Zhang, K Katayama, ... Gastroenterology 160 (6), 2089-2102. e12, 2021 | 66 | 2021 |
| A discriminative latent variable chinese segmenter with hybrid word/character information X Sun, Y Zhang, T Matsuzaki, Y Tsuruoka, J Tsujii Proceedings of Human Language Technologies: The 2009 Annual Conference of …, 2009 | 63 | 2009 |
| The transcriptional landscape of p53 signalling pathway C Tanikawa, Y Zhang, R Yamamoto, Y Tsuda, M Tanaka, Y Funauchi, ... EBioMedicine 20, 109-119, 2017 | 61 | 2017 |
| Nanopore basecalling from a perspective of instance segmentation Y Zhang, A Akdemir, G Tremmel, S Imoto, S Miyano, T Shibuya, ... BMC bioinformatics 21, 1-9, 2020 | 31 | 2020 |
| Sequence-specific bias correction for RNA-seq data using recurrent neural networks Y Zhang, R Yamaguchi, S Imoto, S Miyano BMC genomics 18, 1-6, 2017 | 30 | 2017 |
| Probabilistic Chinese word segmentation with non-local information and stochastic training X Sun, Y Zhang, T Matsuzaki, Y Tsuruoka, J Tsujii Information Processing & Management 49 (3), 626-636, 2013 | 30 | 2013 |
| Identification of bacteriophage genome sequences with representation learning Z Bai, Y Zhang, S Miyano, R Yamaguchi, K Fujimoto, S Uematsu, S Imoto Bioinformatics 38 (18), 4264-4270, 2022 | 20 | 2022 |
| RPI-BLENDER TAC-KBP2013 Knowledge Base Population System. D Yu, H Li, T Cassidy, Q Li, H Huang, Z Chen, H Ji, Y Zhang, D Roth TAC, 2013 | 17 | 2013 |
| Hpsg supertagging: A sequence labeling view Y Zhang, T Matsuzaki, J Tsujii Proceedings of the 11th International Conference on Parsing Technologies …, 2009 | 13 | 2009 |
| On the application of BERT models for nanopore methylation detection Y Zhang, K Yamaguchi, S Hatakeyama, Y Furukawa, S Miyano, ... 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 12 | 2021 |
| Method, program and system for finding correspondence between terms T Nasukawa, RH Rudy, Y Tsuboi, YZ Zhang US Patent 8,682,641, 2014 | 11 | 2014 |
| Identification of a p53-repressed gene module in breast cancer cells T Miyamoto, C Tanikawa, V Yodsurang, YZ Zhang, S Imoto, R Yamaguchi, ... Oncotarget 8 (34), 55821, 2017 | 7 | 2017 |
| A novel approach to quantify calcifications of thyroid nodules in US images based on deep learning: predicting the risk of cervical lymph node metastasis in papillary thyroid … J Wang, C Dong, Y Zhang, L Wang, X Yuan, M He, S Xu, Q Zhou, J Jiang European radiology 33 (12), 9347-9356, 2023 | 6 | 2023 |
| Jun’ichi Tsujii. 2010. A simple approach for HPSG supertagging using dependency information Y Zhang, T Matsuzaki Proceedings of 11th Annual Conference of the North American Chapter of the …, 0 | 5 | |
| Forest-guided supertagger training Y Zhang, T Matsuzaki, J Tsujii Proceedings of the 23rd International Conference on Computational …, 2010 | 4 | 2010 |
| Investigation of the BERT model on nucleotide sequences with non-standard pre-training and evaluation of different k-mer embeddings Y Zhang, Z Bai, S Imoto Bioinformatics 39 (10), btad617, 2023 | 3 | 2023 |
| Imputing time-series microbiome abundance profiles with diffusion model M Seki, YZ Zhang, S Imoto 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2023 | 2 | 2023 |
| Zero-shot-capable identification of phage–host relationships with whole-genome sequence representation by contrastive learning Y Zhang, Y Liu, Z Bai, K Fujimoto, S Uematsu, S Imoto Briefings in Bioinformatics 24 (5), bbad239, 2023 | 2 | 2023 |
