日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Discovering naturally occurring antifreeze peptides from microbiome by integrating protein language models and molecular dynamics simulation

通过整合蛋白质语言模型和分子动力学模拟,从微生物组中发现天然存在的抗冻肽。

Imam, Ibrahim A; Morey, Trevor; Jiang, Yuexu; Wang, Duolin; Xu, Dong; Shao, Qing

S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure

S-PLM:基于序列与结构对比学习的结构感知蛋白质语言模型

Wang, Duolin; Pourmirzaei, Mahdi; Abbas, Usman L; Zeng, Shuai; Manshour, Negin; Esmaili, Farzaneh; Poudel, Biplab; Jiang, Yuexu; Shao, Qing; Chen, Jin; Xu, Dong

IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network

IRnet:基于通路知识的图神经网络的免疫疗法反应预测

Jiang, Yuexu; Immadi, Manish Sridhar; Wang, Duolin; Zeng, Shuai; On Chan, Yen; Zhou, Jing; Xu, Dong; Joshi, Trupti

MULoc-target: Targeting peptide classification and detection using a protein language model

MULoc-target:利用蛋白质语言模型进行靶向肽分类和检测

Jiang, Yuexu; Wang, Duolin; Zeng, Shuai; Zhang, Yichuan; Jiang, Lei; Pourmirzaei, Mahdi; Manshour, Negin; Esmaili, Farzaneh; Zhang, Weinan; Møller, Ian M; Xu, Dong

MTPrompt-PTM: A Multi-Task Method for Post-Translational Modification Prediction Using Prompt Tuning on a Structure-Aware Protein Language Model

MTPrompt-PTM:一种基于结构感知蛋白质语言模型,利用提示调优进行翻译后修饰预测的多任务方法

Han, Ye; He, Fei; Shao, Qing; Wang, Duolin; Xu, Dong

Kinase-substrate prediction using an autoregressive model

利用自回归模型进行激酶底物预测

Esmaili, Farzaneh; Qin, Yongfang; Wang, Duolin; Xu, Dong

Integrating Protein Language Model and Molecular Dynamics Simulations to Discover Antibiofouling Peptides

整合蛋白质语言模型和分子动力学模拟以发现抗生物污损肽

Imam, Ibrahim A; Bailey, Shea; Wang, Duolin; Zeng, Shuai; Xu, Dong; Shao, Qing

ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning

ProtLoc-GRPO:基于图模型和强化学习的细胞系特异性亚细胞定位预测

Zeng, Shuai; Zhang, Weinan; Li, Chaohan; Jiang, Yuexu; Wang, Duolin; Shao, Qing; Xu, Dong

DescribePROT in 2023: more, higher-quality and experimental annotations and improved data download options

2023 年 DescribePROT 项目展望:更多、更高质量的实验性注释以及改进的数据下载选项

Basu, Sushmita; Zhao, Bi; Biró, Bálint; Faraggi, Eshel; Gsponer, Jörg; Hu, Gang; Kloczkowski, Andrzej; Malhis, Nawar; Mirdita, Milot; Söding, Johannes; Steinegger, Martin; Wang, Duolin; Wang, Kui; Xu, Dong; Zhang, Jian; Kurgan, Lukasz

Parameter-efficient fine-tuning on large protein language models improves signal peptide prediction

对大型蛋白质语言模型进行参数高效的微调可提高信号肽预测的准确性

Zeng, Shuai; Wang, Duolin; Jiang, Lei; Xu, Dong