AIMC Topic: Protein Interaction Mapping

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HGLA: Biomolecular Interaction Prediction Based on Mixed High-Order Graph Convolution With Filter Network via LSTM and Channel Attention.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Predicting biomolecular interactions is significant for understanding biological systems. Most existing methods for link prediction are based on graph convolution. Although graph convolution methods are advantageous in extracting structure informatio...
Humans Neural Networks, Computer Protein Interaction Mapping Algorithms Computational Biology
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RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
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 primarily concentr...
Binding Sites Protein Interaction Mapping Algorithms Protein Interaction Maps Proteins Databases, Protein Computational Biology Humans Neural Networks, Computer
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Protein-protein interaction detection using deep learning: A survey, comparative analysis, and experimental evaluation.

Computers in biology and medicine Dec 6, 2024
This survey paper provides a comprehensive analysis of various Deep Learning (DL) techniques and algorithms for detecting protein-protein interactions (PPIs). It examines the scalability, interpretability, accuracy, and efficiency of each technique, ...
Humans Neural Networks, Computer Algorithms Proteins Deep Learning Databases, Protein Computational Biology Protein Interaction Mapping
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ProAffinity-GNN: A Novel Approach to Structure-Based Protein-Protein Binding Affinity Prediction via a Curated Data Set and Graph Neural Networks.

Journal of chemical information and modeling Nov 18, 2024
Protein-protein interactions (PPIs) are crucial for understanding biological processes and disease mechanisms, contributing significantly to advances in protein engineering and drug discovery. The accurate determination of binding affinities, essenti...
Protein Binding Protein Interaction Mapping Neural Networks, Computer Models, Molecular Proteins Protein Conformation Databases, Protein
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Protein-Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools.

Journal of proteome research Nov 11, 2024
The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms, including the binding of antibodies to antigens, enzymes to inhibitors or promoters, and receptors to ligands. Recent studies of PPIs have led to si...
COVID-19 SARS-CoV-2 Databases, Protein Natural Language Processing Protein Interaction Maps Humans Machine Learning Data Mining Protein Interaction Mapping
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LGS-PPIS: A Local-Global Structural Information Aggregation Framework for Predicting Protein-Protein Interaction Sites.

Proteins Nov 9, 2024
Exploring protein-protein interaction sites (PPIS) is of significance to elucidating the intrinsic mechanisms of diverse biological processes. On this basis, recent studies have applied deep learning-based technologies to overcome the high cost of we...
Protein Interaction Mapping Protein Interaction Domains and Motifs Protein Binding Computational Biology Databases, Protein Binding Sites Proteins Algorithms Deep Learning Humans
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Graph-based machine learning model for weight prediction in protein-protein networks.

BMC bioinformatics Nov 8, 2024
Proteins interact with each other in complex ways to perform significant biological functions. These interactions, known as protein-protein interactions (PPIs), can be depicted as a graph where proteins are nodes and their interactions are edges. The...
Computational Biology Databases, Protein Protein Interaction Mapping Saccharomyces cerevisiae Proteins Saccharomyces cerevisiae Machine Learning Algorithms Protein Interaction Maps
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Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction.

Nature communications Nov 7, 2024
Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While...
Algorithms Protein Binding Computational Biology Neural Networks, Computer Machine Learning Protein Interaction Mapping Proteins Models, Molecular
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Protein interactions in human pathogens revealed through deep learning.

Nature microbiology Sep 18, 2024
Identification of bacterial protein-protein interactions and predicting the structures of these complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here we developed RoseTTAFold2-Lit...
Genes, Essential Bacterial Proteins Protein Interaction Mapping Protein Binding Virulence Factors Humans Bacteria Deep Learning Proteome
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Intelligence model on sequence-based prediction of PPI using AISSO deep concept with hyperparameter tuning process.

Scientific reports Sep 18, 2024
Protein-protein interaction (PPI) prediction is vital for interpreting biological activities. Even though many diverse sorts of data and machine learning approaches have been employed in PPI prediction, performance still has to be enhanced. As a resu...
Animals Humans Computational Biology Protein Interaction Mapping Neural Networks, Computer Sharks Machine Learning
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