AIMC Topic: Databases, Protein

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DeepMVD: A Novel Multiview Dynamic Feature Fusion Model for Accurate Protein Function Prediction.

Journal of chemical information and modeling Mar 7, 2025
Proteins, as the fundamental macromolecules of life, play critical roles in various biological processes. Recent advancements in intelligent protein function prediction methods leverage sequences, structures, and biomedical literature data. Among the...
Databases, Protein Computational Biology Proteins Deep Learning
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TrGPCR: GPCR-Ligand Binding Affinity Prediction Based on Dynamic Deep Transfer Learning.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting G protein-coupled receptor (GPCR) -ligand binding affinity plays a crucial role in drug development. However, determining GPCR-ligand binding affinities is time-consuming and resource-intensive. Although many studies used data-driven metho...
Deep Learning Protein Binding Computational Biology Humans Ligands Databases, Protein Receptors, G-Protein-Coupled
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PredIDR2: Improving accuracy of protein intrinsic disorder prediction by updating deep convolutional neural network and supplementing DisProt data.

International journal of biological macromolecules Mar 5, 2025
Intrinsically disordered proteins (IDPs) or regions (IDRs) are widespread in proteomes, and involved in several important biological processes and implicated in many diseases. Many computational methods for IDR prediction are being developed to decre...
Databases, Protein Intrinsically Disordered Proteins Convolutional Neural Networks ROC Curve Computational Biology Neural Networks, Computer Software
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Skittles: GNN-Assisted Pseudo-Ligands Generation and Its Application for Binding Sites Classification and Affinity Prediction.

Proteins Feb 28, 2025
Nowadays, multiple solutions are known for identifying ligand-protein binding sites. Another important task is labeling each point of a binding site with the appropriate atom type, a process known as pseudo-ligand generation. The number of solutions ...
Neural Networks, Computer Machine Learning Models, Molecular Ligands Binding Sites Computational Biology Proteins Databases, Protein Algorithms Protein Binding
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Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance.

Computers in biology and medicine Feb 22, 2025
Peptides are gaining significant attention in diverse fields such as the pharmaceutical market has seen a steady rise in peptide-based therapeutics over the past six decades. Peptides have been utilized in the development of distinct applications inc...
Computational Biology Databases, Protein SARS-CoV-2 Peptides Humans Machine Learning COVID-19 Artificial Intelligence
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Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.

Genome research Feb 14, 2025
Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations...
Animals Metagenomics Rumen Metagenome Ruminants Eukaryota Gastrointestinal Microbiome Databases, Protein Fungi Deep Learning Computational Biology
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Simpler Protein Domain Identification Using Spectral Clustering.

Proteins Feb 13, 2025
The decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is the SPECTRUS algorithm, which provides a segmentation based on spect...
Proteins Databases, Protein Models, Molecular Computational Biology Cluster Analysis Protein Conformation Sequence Alignment Sequence Analysis, Protein Protein Domains Amino Acid Sequence Algorithms Deep Learning
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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...
Artificial Intelligence Protein Interaction Mapping Computational Biology Proteins Databases, Protein Algorithms Protein Interaction Maps
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DOGpred: A Novel Deep Learning Framework for Accurate Identification of Human O-linked Threonine Glycosylation Sites.

Journal of molecular biology Feb 1, 2025
O-linked glycosylation is a crucial post-translational modification that regulates protein function and biological processes. Dysregulation of this process is associated with various diseases, underscoring the need to accurately identify O-linked gly...
Glycosylation Protein Processing, Post-Translational Threonine Databases, Protein Neural Networks, Computer Deep Learning Computational Biology Humans
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KaMLs for Predicting Protein p Values and Ionization States: Are Trees All You Need?

Journal of chemical theory and computation Jan 30, 2025
Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in...
Ions Proteins Machine Learning Databases, Protein Decision Trees Hydrogen-Ion Concentration
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