AIMC Topic: Protein Interaction Mapping

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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...
Protein Interaction Mapping Saccharomyces cerevisiae Proteins Algorithms Protein Interaction Maps Databases, Protein Machine Learning Saccharomyces cerevisiae Computational Biology
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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...
Neural Networks, Computer Machine Learning Algorithms Proteins Models, Molecular Protein Binding Protein Interaction Mapping Computational Biology
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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...
Proteome Genes, Essential Bacterial Proteins Protein Binding Bacteria Virulence Factors Protein Interaction Mapping Humans Deep Learning
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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...
Humans Neural Networks, Computer Machine Learning Protein Interaction Mapping Sharks Animals Computational Biology
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Using AlphaFold Multimer to discover interkingdom protein-protein interactions.

The Plant journal : for cell and molecular biology Aug 17, 2024
Structural prediction by artificial intelligence can be powerful new instruments to discover novel protein-protein interactions, but the community still grapples with the implementation, opportunities and limitations. Here, we discuss and re-analyse ...
Plant Proteins Protein Interaction Mapping Artificial Intelligence Sequence Alignment
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DGCPPISP: a PPI site prediction model based on dynamic graph convolutional network and two-stage transfer learning.

BMC bioinformatics Jul 31, 2024
BACKGROUND: Proteins play a pivotal role in the diverse array of biological processes, making the precise prediction of protein-protein interaction (PPI) sites critical to numerous disciplines including biology, medicine and pharmacy. While deep lear...
Neural Networks, Computer Protein Interaction Mapping Computational Biology Machine Learning Proteins Deep Learning Databases, Protein
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A Hierarchical Graph Neural Network Framework for Predicting Protein-Protein Interaction Modulators With Functional Group Information and Hypergraph Structure.

IEEE journal of biomedical and health informatics Jul 2, 2024
Accurate prediction of small molecule modulators targeting protein-protein interactions (PPIMs) remains a significant challenge in drug discovery. Existing machine learning-based models rely on manual feature engineering, which is tedious and task-sp...
Proteins Protein Interaction Mapping Neural Networks, Computer Protein Interaction Maps Computational Biology Drug Discovery Deep Learning Algorithms
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Protein-Protein Interaction Prediction via Structure-Based Deep Learning.

Proteins Jun 23, 2024
Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with vario...
Protein Interaction Maps Computational Biology Proteins Animals Protein Interaction Mapping Neural Networks, Computer Deep Learning Humans Algorithms Databases, Protein Amino Acid Sequence
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DP-site: A dual deep learning-based method for protein-peptide interaction site prediction.

Methods (San Diego, Calif.) Jun 12, 2024
BACKGROUND: Protein-peptide interaction prediction is an important topic for several applications including various biological processes, understanding drug discovery, protein function abnormal cellular behaviors, and treating diseases. Over the year...
Proteins Databases, Protein Deep Learning Protein Interaction Mapping Software Protein Binding Binding Sites Humans Peptides Computational Biology Neural Networks, Computer
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DSSGNN-PPI: A Protein-Protein Interactions prediction model based on Double Structure and Sequence graph neural networks.

Computers in biology and medicine May 29, 2024
The process of experimentally confirming complex interaction networks among proteins is time-consuming and laborious. This study aims to address Protein-Protein Interactions (PPIs) prediction based on graph neural networks (GNN). A novel multilevel p...
Databases, Protein Protein Interaction Maps Protein Interaction Mapping Humans Computational Biology Neural Networks, Computer Proteins
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