AIMC Topic: Peptides

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IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.

Immunogenetics Jun 24, 2020
Tumor-specific neoantigens are mutated self-peptides presented by tumor cell major histocompatibility complex (MHC) molecules and are necessary to elicit host's anti-cancer cytotoxic T cell responses. It could be specifically recognized by neoantigen...
Computer Simulation Reproducibility of Results Peptides Deep Learning Humans Neural Networks, Computer Alleles Histocompatibility Antigens Class I Amino Acid Sequence Protein Binding Antigens, Neoplasm Databases, Protein
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Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.

Frontiers in immunology Jun 23, 2020
Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adve...
Proteomics Histocompatibility Antigens Class II Peptides Mass Spectrometry Infliximab Humans Dendritic Cells CD4-Positive T-Lymphocytes Antirheumatic Agents Protein Binding Neural Networks, Computer Rituximab Epitopes, T-Lymphocyte
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The proteome landscape of the kingdoms of life.

Nature Jun 17, 2020
Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported, ...
Classification Animals Protein Biosynthesis Species Specificity Proteome Peptides Homeostasis Photosynthesis Oxidation-Reduction Deep Learning Bacteroides Chromatography Ion Transport Iron-Sulfur Proteins Proteolysis Glycolysis Carbohydrate Metabolism Proteomics Protein Folding
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PB-Net: Automatic peak integration by sequential deep learning for multiple reaction monitoring.

Journal of proteomics May 13, 2020
Mass spectrometry (MS) based proteomics has become an indispensable component of modern molecular and cellular biochemistry analysis. Multiple reaction monitoring (MRM) is one of the most well-established MS techniques for molecule detection and quan...
Proteomics Mass Spectrometry Software Humans Peptides Deep Learning
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Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II.

Journal of drug targeting May 1, 2020
Bone morphogenetic protein-2 (BMP-2) is a key regulator of bone formation, growth and regeneration, which contains a conformational wrist epitope and a linear knuckle epitope that are functionally responsible for the protein by mediating its interact...
Epitopes Osteogenesis Crystallization Animals Peptides Mice Bone Morphogenetic Protein Receptors Humans Machine Learning
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Predicting protein-peptide binding sites with a deep convolutional neural network.

Journal of theoretical biology Apr 13, 2020
MOTIVATION: Interactions between proteins and peptides influence biological functions. Predicting such bio-molecular interactions can lead to faster disease prevention and help in drug discovery. Experimental methods for determining protein-peptide b...
Peptides Protein Binding Proteins Neural Networks, Computer Binding Sites
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Energy-based graph convolutional networks for scoring protein docking models.

Proteins Mar 16, 2020
Structural information about protein-protein interactions, often missing at the interactome scale, is important for mechanistic understanding of cells and rational discovery of therapeutics. Protein docking provides a computational alternative for su...
Deep Learning Protein Binding Proteins Benchmarking Structural Homology, Protein Protein Interaction Mapping Research Design Humans Amino Acid Sequence Protein Conformation, alpha-Helical Protein Multimerization Peptides Software Ligands Protein Conformation, beta-Strand Binding Sites Protein Interaction Domains and Motifs Molecular Docking Simulation Thermodynamics Computer Graphics
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DeepAVP: A Dual-Channel Deep Neural Network for Identifying Variable-Length Antiviral Peptides.

IEEE journal of biomedical and health informatics Feb 28, 2020
Antiviral peptides (AVPs) have been experimentally verified to block virus into host cells, which have antiviral activity with decapeptide amide. Therefore, utilization of experimentally validated antiviral peptides is a potential alternative strateg...
Computational Biology Drug Discovery Deep Learning Neural Networks, Computer Antiviral Agents Peptides
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Full-Spectrum Prediction of Peptides Tandem Mass Spectra using Deep Neural Network.

Analytical chemistry Feb 25, 2020
The ability to predict tandem mass (MS/MS) spectra from peptide sequences can significantly enhance our understanding of the peptide fragmentation process and could improve peptide identification in proteomics. However, current approaches for predict...
Tandem Mass Spectrometry Neural Networks, Computer Peptides
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Using isotopic envelopes and neural decision tree-based in silico fractionation for biomolecule classification.

Analytica chimica acta Feb 20, 2020
Untargeted mass spectrometry (MS) workflows are more suitable than targeted workflows for high throughput characterization of complex biological samples. However, analysis workflows for untargeted methods are inadequate for characterization of comple...
Peptides Mass Spectrometry Lipids Neural Networks, Computer Computer Simulation Decision Trees
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