Zobrazeno 1 - 10
of 435
pro vyhledávání: '"Tan Pan"'
Autor:
Yichi Zhang, Jing Wang, Tan Pan, Quanling Jiang, Jingjie Ge, Xin Guo, Chen Jiang, Jie Lu, Jianning Zhang, Xueling Liu, Mei Tian, Yuan Qi, Yuan Cheng, Chuantao Zuo
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-5 (2024)
Abstract Modern facial surgical planning and therapeutic strategies rely heavily on the precise segmentation of the nasal cavity and paranasal sinuses from computed tomography (CT) images for quantitative analysis. Nevertheless, manual segmentation i
Externí odkaz:
https://doaj.org/article/80aabd6f30564fdda2156a102ccd9395
Autor:
Tan, Yang, Li, Mingchen, Zhou, Bingxin, Zhong, Bozitao, Zheng, Lirong, Tan, Pan, Zhou, Ziyi, Yu, Huiqun, Fan, Guisheng, Hong, Liang
Fine-tuning Pre-trained protein language models (PLMs) has emerged as a prominent strategy for enhancing downstream prediction tasks, often outperforming traditional supervised learning approaches. As a widely applied powerful technique in natural la
Externí odkaz:
http://arxiv.org/abs/2404.14850
Accurately modeling the protein fitness landscapes holds great importance for protein engineering. Recently, due to their capacity and representation ability, pre-trained protein language models have achieved state-of-the-art performance in predictin
Externí odkaz:
http://arxiv.org/abs/2402.02004
Publikováno v:
Archives of Biological Sciences, Vol 69, Iss 3, Pp 399-407 (2017)
Klebsiella pneumoniae is a common causative agent of nosocomial infections with a high level of resistance toward β-lactam antibiotics. Our previous study showed that TEM-1 and SHV-11 are the predominant β-lactamase-encoding genes of K. pneumoni
Externí odkaz:
https://doaj.org/article/c3119c8042d14d229d1211920b052988
Large protein language models are adept at capturing the underlying evolutionary information in primary structures, offering significant practical value for protein engineering. Compared to natural language models, protein amino acid sequences have a
Externí odkaz:
http://arxiv.org/abs/2310.17415
Autor:
Jiang, Fan, Li, Mingchen, Dong, Jiajun, Yu, Yuanxi, Sun, Xinyu, Wu, Banghao, Huang, Jin, Kang, Liqi, Pei, Yufeng, Zhang, Liang, Wang, Shaojie, Xu, Wenxue, Xin, Jingyao, Ouyang, Wanli, Fan, Guisheng, Zheng, Lirong, Tan, Yang, Hu, Zhiqiang, Xiong, Yi, Feng, Yan, Yang, Guangyu, Liu, Qian, Song, Jie, Liu, Jia, Hong, Liang, Tan, Pan
Designing protein mutants of both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can suggest protein mutants of improved stability and activity without any
Externí odkaz:
http://arxiv.org/abs/2307.12682
Directed evolution as a widely-used engineering strategy faces obstacles in finding desired mutants from the massive size of candidate modifications. While deep learning methods learn protein contexts to establish feasible searching space, many exist
Externí odkaz:
http://arxiv.org/abs/2304.08299
We introduce TemPL, a novel deep learning approach for zero-shot prediction of protein stability and activity, harnessing temperature-guided language modeling. By assembling an extensive dataset of 96 million sequence-host bacterial strain optimal gr
Externí odkaz:
http://arxiv.org/abs/2304.03780
Publikováno v:
Journal of Cheminformatics (2023) 15:12
Deep learning has been widely used for protein engineering. However, it is limited by the lack of sufficient experimental data to train an accurate model for predicting the functional fitness of high-order mutants. Here, we develop SESNet, a supervis
Externí odkaz:
http://arxiv.org/abs/2301.00004
In the field of face recognition, it is always a hot research topic to improve the loss solution to make the face features extracted by the network have greater discriminative power. Research works in recent years has improved the discriminative powe
Externí odkaz:
http://arxiv.org/abs/2210.02018