AIMC Topic: Peptides

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pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power.

Journal of proteomics Nov 2, 2021
Tandem mass spectrometry has been the principal method in shotgun proteomics for peptide and protein identification. However, incorrect identifications reported by proteome search engines are still unknown, and further validation methods are needed. ...
Software Algorithms Proteomics Proteome Databases, Protein Peptides Deep Learning
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CL-ACP: a parallel combination of CNN and LSTM anticancer peptide recognition model.

BMC bioinformatics Oct 20, 2021
BACKGROUND: Anticancer peptides are defence substances with innate immune functions that can selectively act on cancer cells without harming normal cells and many studies have been conducted to identify anticancer peptides. In this paper, we introduc...
Neural Networks, Computer Amino Acid Sequence Peptides
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Connecting MHC-I-binding motifs with HLA alleles via deep learning.

Communications biology Oct 18, 2021
The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, several predictors have shown impressive performance on binding affinity. However, the decisive MHC residues and their relation to the selection of bin...
Protein Binding Alleles Peptides Deep Learning Genes, MHC Class I Humans
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A heuristic, computer-driven and top-down approach to identify novel bioactive peptides: A proof-of-principle on angiotensin I converting enzyme inhibitory peptides.

Food research international (Ottawa, Ont.) Oct 13, 2021
Bioactive peptides are short peptides (3-20 amino acid residues in length) endowed of specific biological activities. The identification and characterization of bioactive peptides of food origin are crucial to better understand the physiological cons...
Computer Heuristics Dietary Supplements Peptidyl-Dipeptidase A Computers Peptides
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Anti-cancer Peptide Recognition Based on Grouped Sequence and Spatial Dimension Integrated Networks.

Interdisciplinary sciences, computational life sciences Oct 12, 2021
The diversification of the characteristic sequences of anti-cancer peptides has imposed difficulties on research. To effectively predict new anti-cancer peptides, this paper proposes a more suitable feature grouping sequence and spatial dimension-int...
Peptides Amino Acid Sequence Neural Networks, Computer Algorithms
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Prediction for understanding the effectiveness of antiviral peptides.

Computational biology and chemistry Oct 8, 2021
The low efficacy of current antivirals in conjunction with the resistance of viruses against existing antiviral drugs has resulted in the demand for the development of novel antiviral agents. Antiviral peptides (AVPs) are those bioactive peptides hav...
Algorithms Peptides Antiviral Agents Machine Learning Computational Biology Hydrophobic and Hydrophilic Interactions
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AIEpred: An Ensemble Predictive Model of Classifier Chain to Identify Anti-Inflammatory Peptides.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Anti-inflammatory peptides (AIEs) have recently emerged as promising therapeutic agent for treatment of various inflammatory diseases, such as rheumatoid arthritis and Alzheimer's disease. Therefore, detecting the correlation between amino acid seque...
Computational Biology Models, Statistical Peptides Amino Acid Sequence Anti-Inflammatory Agents Drug Discovery Sequence Analysis, Protein Machine Learning Algorithms
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PredAPP: Predicting Anti-Parasitic Peptides with Undersampling and Ensemble Approaches.

Interdisciplinary sciences, computational life sciences Oct 4, 2021
Anti-parasitic peptides (APPs) have been regarded as promising therapeutic candidate drugs against parasitic diseases. Due to the fact that the experimental techniques for identifying APPs are expensive and time-consuming, there is an urgent need to ...
Peptides Logistic Models Algorithms Computers Machine Learning
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A deep-learning framework for multi-level peptide-protein interaction prediction.

Nature communications Sep 15, 2021
Peptide-protein interactions are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. Recently, a number of computational methods have been developed to predict peptide...
Computational Biology Proteins Protein Domains Binding Sites Models, Molecular Deep Learning Protein Binding Reproducibility of Results Algorithms Peptides
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T Cell Epitope Prediction and Its Application to Immunotherapy.

Frontiers in immunology Sep 15, 2021
T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for ep...
Mass Spectrometry Peptides Models, Molecular Neoplasms Computational Biology Receptors, Antigen, T-Cell Antigens, Neoplasm Antigen Presentation Epitopes, T-Lymphocyte Immunotherapy Humans Sequence Analysis, DNA T-Cell Antigen Receptor Specificity Histocompatibility Antigens Class I Neural Networks, Computer Base Sequence
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