AIMC Topic: Protein Interaction Mapping

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A Multimodal Deep Learning Framework for Predicting PPI-Modulator Interactions.

Journal of chemical information and modeling Dec 1, 2023
Protein-protein interactions (PPIs) are essential for various biological processes and diseases. However, most existing computational methods for identifying PPI modulators require either target structure or reference modulators, which restricts thei...
Molecular Docking Simulation Protein Interaction Mapping Kelch-Like ECH-Associated Protein 1 Deep Learning NF-E2-Related Factor 2
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CSM-Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces.

Proteins Oct 23, 2023
Proteins are molecular machinery that participate in virtually all essential biological functions within the cell, which are tightly related to their 3D structure. The importance of understanding protein structure-function relationship is highlighted...
Computational Biology Proteins Deep Learning Protein Binding Ligands Protein Conformation Databases, Protein Models, Molecular Humans Software Protein Interaction Domains and Motifs Binding Sites Protein Interaction Mapping
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Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
Protein-protein interactions (PPIs) play a critical role in the proteomics study, and a variety of computational algorithms have been developed to predict PPIs. Though effective, their performance is constrained by high false-positive and false-negat...
Proteins Protein Interaction Mapping Neural Networks, Computer Algorithms
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DensePPI: A Novel Image-Based Deep Learning Method for Prediction of Protein-Protein Interactions.

IEEE transactions on nanobioscience Oct 3, 2023
Protein-protein interactions (PPI) are crucial for understanding the behaviour of living organisms and identifying disease associations. This paper proposes DensePPI, a novel deep convolution strategy applied to the 2D image map generated from the in...
Protein Interaction Mapping Proteins Caenorhabditis elegans Animals Deep Learning Humans Mice Escherichia coli
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Recent advances in predicting and modeling protein-protein interactions.

Trends in biochemical sciences Apr 14, 2023
Protein-protein interactions (PPIs) drive biological processes, and disruption of PPIs can cause disease. With recent breakthroughs in structure prediction and a deluge of genomic sequence data, computational methods to predict PPIs and model spatial...
Artificial Intelligence Protein Interaction Mapping Computational Biology Machine Learning Proteome Algorithms
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Graph-BERT and language model-based framework for protein-protein interaction identification.

Scientific reports Apr 6, 2023
Identification of protein-protein interactions (PPI) is among the critical problems in the domain of bioinformatics. Previous studies have utilized different AI-based models for PPI classification with advances in artificial intelligence (AI) techniq...
Amino Acid Sequence Protein Interaction Mapping Artificial Intelligence Protein Interaction Maps Proteins
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Cracking the code of cellular protein-protein interactions: Alphafold and whole-cell crosslinking to the rescue.

Molecular systems biology Mar 10, 2023
Integration of experimental and computational methods is crucial to better understanding protein-protein interactions (PPIs), ideally in their cellular context. In their recent work, Rappsilber and colleagues (O'Reilly et al, 2023) identified bacteri...
Artificial Intelligence Proteins Protein Interaction Mapping
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Hierarchical graph learning for protein-protein interaction.

Nature communications Feb 25, 2023
Protein-Protein Interactions (PPIs) are fundamental means of functions and signalings in biological systems. The massive growth in demand and cost associated with experimental PPI studies calls for computational tools for automated prediction and und...
Amino Acid Sequence Humans Protein Interaction Mapping Deep Learning Protein Interaction Maps Proteins
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ISPRED-SEQ: Deep Neural Networks and Embeddings for Predicting Interaction Sites in Protein Sequences.

Journal of molecular biology Jan 13, 2023
The knowledge of protein-protein interaction sites (PPIs) is crucial for protein functional annotation. Here we address the problem focusing on the prediction of putative PPIs considering as input protein sequences. The issue is important given the h...
Proteins Amino Acid Sequence Deep Learning Molecular Sequence Annotation Protein Interaction Mapping
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SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction.

BMC genomics Jun 27, 2022
BACKGROUND: Protein-protein interactions (PPIs) dominate intracellular molecules to perform a series of tasks such as transcriptional regulation, information transduction, and drug signalling. The traditional wet experiment method to obtain PPIs info...
Mice Protein Interaction Mapping Computational Biology Neural Networks, Computer Humans Amino Acid Sequence Animals Saccharomyces cerevisiae
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