AIMC Topic: Protein Interaction Mapping

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Explainability of Protein Deep Learning Models.

International journal of molecular sciences May 29, 2025
Protein embeddings are the new main source of information about proteins, producing state-of-the-art solutions to many problems, including protein interaction prediction, a fundamental issue in proteomics. Understanding the embeddings and what causes...
Proteomics Proteins Deep Learning Protein Interaction Mapping Hydrophobic and Hydrophilic Interactions Computational Biology
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Predicting protein-protein interaction with interpretable bilinear attention network.

Computer methods and programs in biomedicine Mar 30, 2025
BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biological processes, helping to understand the protein function and disease pathology. Identification of PPIs and their interaction types through wet experime...
Deep Learning Humans Protein Binding Computational Biology Neural Networks, Computer Algorithms Databases, Protein Proteins Amino Acid Sequence Protein Interaction Mapping Sequence Analysis, Protein Protein Conformation
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SEGT-GO: a graph transformer method based on PPI serialization and explanatory artificial intelligence for protein function prediction.

BMC bioinformatics Feb 10, 2025
BACKGROUND: A massive amount of protein sequences have been obtained, but their functions remain challenging to discern. In recent research on protein function prediction, Protein-Protein Interaction (PPI) Networks have played a crucial role. Uncover...
Algorithms Protein Interaction Maps Computational Biology Artificial Intelligence Protein Interaction Mapping Proteins Databases, Protein
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Deep learning methods for proteome-scale interaction prediction.

Current opinion in structural biology Jan 22, 2025
Proteome-scale interaction prediction is essential for understanding protein functions and disease mechanisms. Traditional experimental methods are often limited by scale and complexity, driving the need for computational approaches. Deep learning ha...
Proteome Proteins Protein Interaction Mapping Protein Binding Computational Biology Humans Deep Learning
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MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.

International journal of biological macromolecules Jan 21, 2025
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental metho...
Proteins Neural Networks, Computer Models, Molecular Algorithms Protein Conformation Graph Neural Networks Binding Sites Protein Binding Protein Interaction Mapping Computational Biology
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PPILS: Protein-protein interaction prediction with language of biological coding.

Computers in biology and medicine Jan 19, 2025
Protein-protein interactions within a cell are essential for various fundamental biological processes. Computational techniques have arisen in bioinformatics due to the challenging and resource-intensive nature of experimental protein pair interactio...
Humans Machine Learning Computational Biology Proteins Protein Interaction Maps Databases, Protein Protein Interaction Mapping
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Supervised learning approaches for predicting Ebola-Human Protein-Protein interactions.

Gene Jan 17, 2025
The goal of this research work is to predict protein-protein interactions (PPIs) between the Ebola virus and the host who is at risk of infection. Since there are very limited databases available on the Ebola virus; we have prepared a comprehensive d...
Hemorrhagic Fever, Ebola Viral Proteins Protein Interaction Mapping Databases, Protein Supervised Machine Learning Support Vector Machine Ebolavirus Gene Ontology Host-Pathogen Interactions Humans Protein Interaction Maps Computational Biology
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Structure-Based Approaches for Protein-Protein Interaction Prediction Using Machine Learning and Deep Learning.

Biomolecules Jan 17, 2025
Protein-Protein Interaction (PPI) prediction plays a pivotal role in understanding cellular processes and uncovering molecular mechanisms underlying health and disease. Structure-based PPI prediction has emerged as a robust alternative to sequence-ba...
Proteins Protein Conformation Protein Interaction Mapping Humans Deep Learning Machine Learning Computational Biology Proteomics
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MAGPIE: A Machine Learning Approach to Decipher Protein-Protein Interactions in Human Plasma.

Journal of proteome research Jan 7, 2025
Immunoprecipitation coupled to tandem mass spectrometry (IP-MS/MS) methods are often used to identify protein-protein interactions (PPIs). While these approaches are prone to false positive identifications through contamination and antibody nonspecif...
Immunoprecipitation Protein Interaction Mapping Algorithms Protein Interaction Maps Blood Proteins Tandem Mass Spectrometry Proteomics Humans Machine Learning
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Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Journal of chemical information and modeling Jan 7, 2025
Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters is essential for elucidating complex protein interactions and for the targeted screening of peptide- or protein-based drugs. We introduce MCGLPPI++, a ...
Machine Learning Receptors, Antigen, T-Cell Protein Binding Protein Interaction Mapping Proteins
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