Zobrazeno 1 - 10
of 276
pro vyhledávání: '"Kenta Nakai"'
Autor:
Junichi Iwata, Kenta Nakai
Publikováno v:
Frontiers in Genetics, Vol 15 (2024)
Externí odkaz:
https://doaj.org/article/96df4e5947cb4df1beea1335c760cb80
Publikováno v:
Frontiers in Genetics, Vol 15 (2024)
The detection of enhancer-promoter interactions (EPIs) is crucial for understanding gene expression regulation, disease mechanisms, and more. In this study, we developed TF-EPI, a deep learning model based on Transformer designed to detect these inte
Externí odkaz:
https://doaj.org/article/26880f4881ac40ff9c43296cd02ef917
Autor:
Yutong Dai, Jingmei Li, Keita Yamamoto, Susumu Goyama, Martin Loza, Sung-Joon Park, Kenta Nakai
Publikováno v:
Frontiers in Genetics, Vol 15 (2024)
Preventing, diagnosing, and treating diseases requires accurate clinical biomarkers, which remains challenging. Recently, advanced computational approaches have accelerated the discovery of promising biomarkers from high-dimensional multimodal data.
Externí odkaz:
https://doaj.org/article/b780abff97f8444c872afca35ce17ec5
Autor:
Yubo Zhang, Wenbo Yang, Yutaro Kumagai, Martin Loza, Weihang Zhang, Sung-Joon Park, Kenta Nakai
Publikováno v:
Frontiers in Immunology, Vol 14 (2023)
Macrophages display extreme plasticity, and the mechanisms and applications of polarization and de-/repolarization of macrophages have been extensively investigated. However, the regulation of macrophage hysteresis after de-/repolarization remains un
Externí odkaz:
https://doaj.org/article/962d4203d85f4cad8ef6cc96f355d7e9
Autor:
Junru Jin, Yingying Yu, Ruheng Wang, Xin Zeng, Chao Pang, Yi Jiang, Zhongshen Li, Yutong Dai, Ran Su, Quan Zou, Kenta Nakai, Leyi Wei
Publikováno v:
Genome Biology, Vol 23, Iss 1, Pp 1-23 (2022)
Abstract In this study, we propose iDNA-ABF, a multi-scale deep biological language learning model that enables the interpretable prediction of DNA methylations based on genomic sequences only. Benchmarking comparisons show that our iDNA-ABF outperfo
Externí odkaz:
https://doaj.org/article/2f80a30227c3499ab9491653447fcbb1
Autor:
Yuji Kubota, Yuko Fujioka, Ashwini Patil, Yusuke Takagi, Daisuke Matsubara, Masatomi Iijima, Isao Momose, Ryosuke Naka, Kenta Nakai, Nobuo N. Noda, Mutsuhiro Takekawa
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-19 (2022)
MEK1 mutations are found in cancer and RASopathies, but their effects remain unclear. Here, the authors reveal a mutant MEK1 structure and qualitative differences in biological properties between the cancer- and RASopathy-associated mutants, providin
Externí odkaz:
https://doaj.org/article/9947a9cf2139440e875defedf512d313
Publikováno v:
BMC Bioinformatics, Vol 22, Iss S6, Pp 1-12 (2021)
Abstract Background Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed t
Externí odkaz:
https://doaj.org/article/1ce41be56a654eaf8af4bf957c51e85c
Autor:
Ryo Kinoshita-Daitoku, Kotaro Kiga, Masatoshi Miyakoshi, Ryota Otsubo, Yoshitoshi Ogura, Takahito Sanada, Zhu Bo, Tuan Vo Phuoc, Tokuju Okano, Tamako Iida, Rui Yokomori, Eisuke Kuroda, Sayaka Hirukawa, Mototsugu Tanaka, Arpana Sood, Phawinee Subsomwong, Hiroshi Ashida, Tran Thanh Binh, Lam Tung Nguyen, Khien Vu Van, Dang Quy Dung Ho, Kenta Nakai, Toshihiko Suzuki, Yoshio Yamaoka, Tetsuya Hayashi, Hitomi Mimuro
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
Long-term infection of the stomach with Helicobacter pylori can cause gastric cancer. Here, Kinoshita-Daitoku et al. show that a small non-coding RNA of H. pylori regulates bacterial adaptation to the stomach environment and bacterial oncoprotein pro
Externí odkaz:
https://doaj.org/article/c638c303a9cd4ae1863ee6c625b9c70d
Autor:
Kenta Nakai, Leyi Wei
Publikováno v:
Frontiers in Bioinformatics, Vol 2 (2022)
Prediction of subcellular localization of proteins from their amino acid sequences has a long history in bioinformatics and is still actively developing, incorporating the latest advances in machine learning and proteomics. Notably, deep learning-bas
Externí odkaz:
https://doaj.org/article/4674aeaf89444f1eb0a70d830d2eed76
Autor:
Satoru Onizuka, Yasuharu Yamazaki, Sung-Joon Park, Takayuki Sugimoto, Yumiko Sone, Sebastian Sjöqvist, Michihiko Usui, Akira Takeda, Kenta Nakai, Keisuke Nakashima, Takanori Iwata
Publikováno v:
BMC Genomics, Vol 21, Iss 1, Pp 1-4 (2020)
An amendment to this paper has been published and can be accessed via the original article.
Externí odkaz:
https://doaj.org/article/b25256625694455d9fab8afae4561644