AIMC Topic: Databases, Protein

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PredIDR: Accurate prediction of protein intrinsic disorder regions using deep convolutional neural network.

International journal of biological macromolecules Nov 19, 2024
The involvement of protein intrinsic disorder in essential biological processes, it is well known in structural biology. However, experimental methods for detecting intrinsic structural disorder and directly measuring highly dynamic behavior of prote...
Intrinsically Disordered Proteins Neural Networks, Computer Computational Biology Proteins Databases, Protein Software Algorithms
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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...
Neural Networks, Computer Proteins Databases, Protein Protein Binding Protein Interaction Mapping Models, Molecular Protein Conformation
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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...
Databases, Protein Natural Language Processing Protein Interaction Mapping Data Mining COVID-19 SARS-CoV-2 Protein Interaction Maps Humans Machine Learning
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DeepBP: Ensemble deep learning strategy for bioactive peptide prediction.

BMC bioinformatics Nov 11, 2024
BACKGROUND: Bioactive peptides are important bioactive molecules composed of short-chain amino acids that play various crucial roles in the body, such as regulating physiological processes and promoting immune responses and antibacterial effects. Due...
Antineoplastic Agents Neural Networks, Computer Databases, Protein Deep Learning Peptides Angiotensin-Converting Enzyme Inhibitors Computational Biology
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Improving drug-target interaction prediction through dual-modality fusion with InteractNet.

Journal of bioinformatics and computational biology Nov 11, 2024
In the drug discovery process, accurate prediction of drug-target interactions is crucial to accelerate the development of new drugs. However, existing methods still face many challenges in dealing with complex biomolecular interactions. To this end,...
Binding Sites Deep Learning Protein Binding Proteins Pharmaceutical Preparations Machine Learning Databases, Protein Ligands Computational Biology Humans Algorithms Neural Networks, Computer Drug Discovery
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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 Binding Computational Biology Proteins Algorithms Deep Learning Protein Interaction Mapping Protein Interaction Domains and Motifs Databases, Protein Binding Sites Humans
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Deep-GB: A novel deep learning model for globular protein prediction using CNN-BiLSTM architecture and enhanced PSSM with trisection strategy.

IET systems biology Nov 8, 2024
Globular proteins (GPs) play vital roles in a wide range of biological processes, encompassing enzymatic catalysis and immune responses. Enzymes, among these globular proteins, facilitate biochemical reactions, while others, such as haemoglobin, cont...
Neural Networks, Computer Proteins Databases, Protein Position-Specific Scoring Matrices Deep Learning Computational Biology
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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...
Saccharomyces cerevisiae Proteins Saccharomyces cerevisiae Machine Learning Protein Interaction Mapping Algorithms Computational Biology Databases, Protein Protein Interaction Maps
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TPGPred: A Mixed-Feature-Driven Approach for Identifying Thermophilic Proteins Based on GradientBoosting.

International journal of molecular sciences Nov 5, 2024
Thermophilic proteins maintain their stability and functionality under extreme high-temperature conditions, making them of significant importance in both fundamental biological research and biotechnological applications. In this study, we developed a...
Machine Learning Proteins Algorithms Databases, Protein ROC Curve Computational Biology
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Challenge for Deep Learning: Protein Structure Prediction of Ligand-Induced Conformational Changes at Allosteric and Orthosteric Sites.

Journal of chemical information and modeling Nov 1, 2024
In the realm of biomedical research, understanding the intricate structure of proteins is crucial, as these structures determine how proteins function within our bodies and interact with potential drugs. Traditionally, methods like X-ray crystallogra...
Deep Learning Proteins Ligands Protein Conformation Allosteric Site Databases, Protein Models, Molecular
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