Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction [0.03%]
基于蛋白质内部和之间图表示学习的结合位点预测方法
Wenting Zhao,Gongping Xu,Long Wang et al.
Wenting Zhao et al.
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we ...
SAGCN: Using graph convolutional network with subgraph-aware for circRNA-drug sensitivity identification [0.03%]
基于子图感知的图卷积网络用于环状rna-药物敏感性识别
Weicheng Sun,Chengjuan Ren,Jinsheng Xu et al.
Weicheng Sun et al.
Circular RNAs (circRNAs) play a significant role in cancer development and therapy resistance. There is substantial evidence indicating that the expression of circRNAs affects the sensitivity of cells to drugs. Identifying circRNAs-drug sen...
Recursive Self-Composite Approach Towards Structural Understanding of Boolean Networks [0.03%]
一种递归自包含方法促进布尔网络的结构分析
Jongrae Kim,Woojeong Lee,Kwang-Hyun Cho
Jongrae Kim
Boolean networks have been widely used in systems biology to study the dynamical characteristics of biological networks such as steady-states or cycles, yet there has been little attention to the dynamic properties of network structures. He...
PRFold-TNN: Protein Fold Recognition With an Ensemble Feature Selection Method Using PageRank Algorithm Based on Transformer [0.03%]
基于Transformer的PageRank算法集成特征选择方法的蛋白质折叠识别模型 PRFold-TNN
Xinyi Qin,Lu Zhang,Min Liu et al.
Xinyi Qin et al.
Understanding the tertiary structures of proteins is of great benefit to function in many aspects of human life. Protein fold recognition is a vital and salient means to know protein structure. Until now, researchers have successively propo...
SIG: Graph-Based Cancer Subtype Stratification With Gene Mutation Structural Information [0.03%]
基于图的癌症亚型分类方法及其结构性基因突变信息
Chengcheng Zhang,Wei Li,Ming Deng et al.
Chengcheng Zhang et al.
Somatic tumors have a high-dimensional, sparse, and small sample size nature, making cancer subtype stratification based on somatic genomic data a challenge. Current methods for improving cancer clustering performance focus on dimension red...
Novel Antimicrobial Peptide Design Using Motif Match Score Representation [0.03%]
基于 motif 匹配评分的新抗菌肽设计
Ummu Gulsum Soylemez,Malik Yousef,Burcu Bakir-Gungor
Ummu Gulsum Soylemez
Antimicrobial peptides (AMPs) have drawn the interest of the researchers since they offer an alternative to the traditional antibiotics in the fight against antibiotic resistance and they exhibit additional pharmaceutically significant prop...
Distantly Supervised Biomedical Relation Extraction Via Negative Learning and Noisy Student Self-Training [0.03%]
基于负例学习和 noisy student 自训练的远监督生物医学关系抽取方法
Yuanfei Dai,Bin Zhang,Shiping Wang
Yuanfei Dai
Biomedical relation extraction aims to identify underlying relationships among entities, such as gene associations and drug interactions, within biomedical texts. Despite advancements in relation extraction in general knowledge domains, the...
Prediction of Inter-residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning [0.03%]
基于深度学习的蛋白质多残基距离预测及构象研究
Fujin Zhang,Zhangwei Li,Kailong Zhao et al.
Fujin Zhang et al.
AlphaFold2 has achieved a major breakthrough in end-to-end prediction for static protein structures. However, protein conformational change is considered to be a key factor in protein biological function. Inter-residue multiple distances pr...
Mohamed Divan Masood,Manjula,Vijayan Sugumaran
Mohamed Divan Masood
Controlling the gene expression is the most important development in a living organism, which makes it easier to find different kinds of diseases and their causes. It's very difficult to know what factors control the gene expression. Transc...
RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction [0.03%]
基于残差图卷积网络的蛋白质相互作用位点预测模型
Jian Zhong,Haochen Zhao,Qichang Zhao et al.
Jian Zhong et al.
Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms of biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primaril...