iEnhancer-Flow: Integrating Transformer-Based Sequence Learning with DNA Shape Insights for Robust Enhancer Prediction [0.03%]
基于Transformer的序列学习与DNA形状洞察整合的增强子预测方法(iEnhancer-Flow)
Huan Liu,Hanyu Luo,Lingyun Luo et al.
Huan Liu et al.
Purpose: Enhancers are critical non-coding regulatory elements, but their prediction remains challenging due to their variability and the absence of clear sequence motifs. This study aims to promote enhancer classificatio...
IMF-DDI: Information Mapping and Fusion Framework for Drug-drug Interaction Prediction [0.03%]
基于信息映射和融合的药物相互作用预测框架
Xiaoyang Li,Yuhao Zhang,Yafei Liu et al.
Xiaoyang Li et al.
Drug-drug interactions (DDIs) are crucial throughout various stages of drug development. Using computer-aided methods for accurate prediction of DDIs can enhance clinical safety and accelerate drug discovery. However, most existing deep lea...
Subtype-HM: A Novel Cancer Subtype Identification Method Based on Hypergraph Learning and Multi-omics Data [0.03%]
基于超图学习和多组学数据的新型癌症亚型识别方法subtype-hm
Jie Wang,Xin Huang,Hulin Kuang et al.
Jie Wang et al.
Cancer is a complex and lethal disease influenced by multiple factors, and accurate subtyping is crucial for personalized treatment and prognostic evaluation. Although deep learning has made progress in cancer subtype identification, existi...
HPCSMN: A Classification Method of Chemotherapy Sensitivity of Hypopharyngeal Cancer Based on Multimodal Network [0.03%]
基于多模态网络的下咽癌化疗敏感性分类方法HPCSMN
Weiqi Fu,Haiyan Li,Xiongwen Quan et al.
Weiqi Fu et al.
The treatment of hypopharyngeal cancer faces complex challenges, and accurate prediction of chemotherapy sensitivity is crucial for personalized treatment. In this study, a multimodal fusion network based on deep learning was used to classi...
MED-PPIS: Multi-order Moments External Graph Attention Network with Dual-Axis Attention for Protein-Protein Interaction Site Prediction [0.03%]
基于双轴注意力的多阶矩外部图注意力网络蛋白质互作位点预测方法
Dangguo Shao,Yuyang Zou,Lei Ma et al.
Dangguo Shao et al.
Accurate prediction of protein-protein interaction (PPI) sites is fundamental to elucidating cellular mechanisms and advancing genomics. However, prevailing graph neural networks are constrained by two key limitations: they often neglect la...
GSF-DTA: An Innovative Graph-Sequence Fusion Framework for Drug-Target Affinity Prediction [0.03%]
GSF-DTA：一种创新的图序列融合框架用于药物-靶点亲和力预测
Guiyang Zhang,Yuemei Wang,Danni Zhao et al.
Guiyang Zhang et al.
Drug development is a lengthy and intricate process, where predicting drug-target affinity (DTA) is a vital step. Although traditional experimental techniques yield accurate and reliable results, their high cost and limited throughput rende...
GapSense: Similarity Estimation-Based Gap Filler with TGS-Reads for Genome Assemblies [0.03%]
基于相似性估计的缺口填补方法GapSense及其在染色体水平基因组组装中的应用
Yejin Kan,Dongyeon Kim,Jinkyung Yang et al.
Yejin Kan et al.
Advances in next-generation sequencing have led to an explosion in sequencing data, accelerating genome assembly research. However, draft genomes generated after scaffolding still contain unresolved gaps, often caused by repetitive regions ...
Subgraph Neural Networks Enhanced by Global Similarity for Drug Repositioning [0.03%]
基于全局相似性的子图神经网络在药物重定位中的应用研究
Chengyan Zhou,Xinliang Sun,Xiang Du et al.
Chengyan Zhou et al.
Drug repositioning is a promising strategy for accelerating drug development and reducing costs by identifying potential indications for existing drugs. Recently, technological advancements have enabled the development of numerous graph con...
MDL-HTI: A Multimodal Deep Learning Approach for Predicting Herb-Target Interactions [0.03%]
一种用于预测药食同源的多模态深度学习方法 MDL-HTI
Lianzhong Zhang,Xiumin Shi,Xiaohong Deng
Lianzhong Zhang
Purpose: Traditional Chinese medicine (TCM) has garnered increasing attention from the global medical community due to its unique therapeutic principles and extensive medicinal resources. Understanding herb-target interac...
Joint Low Rank Representation with Symmetric Orthogonal Decomposition for Clustering of scRNA-seq Data [0.03%]
基于对称正交分解的联合低秩表示的单细胞数据聚类方法
Wei Zhang,Yue Yu,Yuanyuan Li et al.
Wei Zhang et al.
Single-cell RNA transcriptome data offer a fantastic chance to investigate biological mechanisms such as cellular heterogeneity. Accurate identification of subtypes is of great importance for revealing the molecular mechanisms underlying co...