AIMC Topic: Databases, Protein

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NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

Journal of proteome research Dec 31, 2024
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on im...
Software Peptides Deep Learning Databases, Protein Tandem Mass Spectrometry Sequence Analysis, Protein Proteomics Cluster Analysis
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Site-specific prediction of O-GlcNAc modification in proteins using evolutionary scale model.

PloS one Dec 31, 2024
Protein glycosylation, a vital post-translational modification, is pivotal in various biological processes and disease pathogenesis. Computational approaches, including protein language models and machine learning algorithms, have emerged as valuable...
Proteins Databases, Protein Glycosylation Algorithms Protein Processing, Post-Translational Glycoproteins Acetylglucosamine Computational Biology Humans Evolution, Molecular Machine Learning
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Topology-based protein classification: A deep learning approach.

Biochemical and biophysical research communications Dec 24, 2024
Utilizing Artificial Intelligence (AI) in computational biology techniques could offer significant advantages in alleviating the growing workloads faced by structural biologists, especially with the emergence of big data. In this study, we employed D...
Databases, Protein Protein Conformation Neural Networks, Computer Computational Biology Proteins Deep Learning
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Improved enzyme functional annotation prediction using contrastive learning with structural inference.

Communications biology Dec 23, 2024
Recent years have witnessed the remarkable progress of deep learning within the realm of scientific disciplines, yielding a wealth of promising outcomes. A prominent challenge within this domain has been the task of predicting enzyme function, a comp...
Amino Acid Sequence Molecular Sequence Annotation Prochlorococcus Enzymes Proteome Deep Learning Databases, Protein Computational Biology
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PTSP-BERT: Predict the thermal stability of proteins using sequence-based bidirectional representations from transformer-embedded features.

Computers in biology and medicine Dec 20, 2024
Thermophilic proteins, mesophiles proteins and psychrophilic proteins have wide industrial applications, as enzymes with different optimal temperatures are often needed for different purposes. Convenient methods are needed to determine the optimal te...
Protein Stability Proteins Databases, Protein Deep Learning
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DeepPD: A Deep Learning Method for Predicting Peptide Detectability Based on Multi-feature Representation and Information Bottleneck.

Interdisciplinary sciences, computational life sciences Dec 11, 2024
Peptide detectability measures the relationship between the protein composition and abundance in the sample and the peptides identified during the analytical procedure. This relationship has significant implications for the fundamental tasks of prote...
Humans Algorithms Computational Biology Proteomics Peptides Databases, Protein Deep Learning
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An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling networks, disease processes, and drug development, as they represent the physical contacts and functional associations between proteins. Recent advances...
Protein Interaction Mapping Graph Neural Networks Humans Neural Networks, Computer Computational Biology Algorithms Proteins Protein Interaction Maps Databases, Protein
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A Protein-Context Enhanced Master Slave Framework for Zero-Shot Drug Target Interaction Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Drug Target Interaction (DTI) prediction plays a crucial role in in-silico drug discovery, especially for deep learning (DL) models. Along this line, existing methods usually first extract features from drugs and target proteins, and use drug-target ...
Drug Discovery Deep Learning Proteins Databases, Protein Computational Biology Ligands Humans Algorithms
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Improving Antifreeze Proteins Prediction With Protein Language Models and Hybrid Feature Extraction Networks.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate identification of antifreeze proteins (AFPs) is crucial in developing biomimetic synthetic anti-icing materials and low-temperature organ preservation materials. Although numerous machine learning-based methods have been proposed for AFPs pr...
Databases, Protein Sequence Analysis, Protein Antifreeze Proteins Algorithms Deep Learning Neural Networks, Computer Computational Biology
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Parallel Convolutional Contrastive Learning Method for Enzyme Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The function labeling of enzymes has a wide range of application value in the medical field, industrial biology and other fields. Scientists define enzyme categories by enzyme commission (EC) numbers. At present, although there are some tools for enz...
Enzymes Computational Biology Databases, Protein Algorithms Deep Learning Neural Networks, Computer Machine Learning
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