AIMC Topic: Protein Processing, Post-Translational

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Exploring the roles of ribosomal peptides in prokaryote-phage interactions through deep learning-enabled metagenome mining.

Microbiome May 24, 2024
BACKGROUND: Microbial secondary metabolites play a crucial role in the intricate interactions within the natural environment. Among these metabolites, ribosomally synthesized and post-translationally modified peptides (RiPPs) are becoming a promising...
Protein Processing, Post-Translational Microbiota Metagenomics Deep Learning Bacteria Oceans and Seas Metagenome Ribosomes Seawater Peptides Bacteriophages
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KbhbXG: A Machine learning architecture based on XGBoost for prediction of lysine β-Hydroxybutyrylation (Kbhb) modification sites.

Methods (San Diego, Calif.) Apr 27, 2024
Lysine β-hydroxybutyrylation is an important post-translational modification (PTM) involved in various physiological and biological processes. In this research, we introduce a novel predictor KbhbXG, which utilizes XGBoost to identify β-hydroxybutyry...
Machine Learning Software Humans Proteomics Protein Processing, Post-Translational Lysine Algorithms Computational Biology
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Predicting lysine methylation sites using a convolutional neural network.

Methods (San Diego, Calif.) Apr 9, 2024
Protein lysine methylation is a particular type of post translational modification that plays an important role in both histone and non-histone function regulation in proteins. Deregulation caused by lysine methyltransferases has been identified as t...
Protein Processing, Post-Translational Methylation Histone-Lysine N-Methyltransferase Machine Learning Lysine Humans Computational Biology Neural Networks, Computer
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Prediction of protein N-terminal acetylation modification sites based on CNN-BiLSTM-attention model.

Computers in biology and medicine Mar 21, 2024
N-terminal acetylation is one of the most common and important post-translational modifications (PTM) of eukaryotic proteins. PTM plays a crucial role in various cellular processes and disease pathogenesis. Thus, the accurate identification of N-term...
Neural Networks, Computer Algorithms Humans Acetylation Proteins Deep Learning Databases, Protein Protein Processing, Post-Translational
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Identifying Protein Phosphorylation Site-Disease Associations Based on Multi-Similarity Fusion and Negative Sample Selection by Convolutional Neural Network.

Interdisciplinary sciences, computational life sciences Mar 8, 2024
As one of the most important post-translational modifications (PTMs), protein phosphorylation plays a key role in a variety of biological processes. Many studies have shown that protein phosphorylation is associated with various human diseases. There...
Alzheimer Disease ROC Curve Computational Biology Proteins Phosphorylation Protein Processing, Post-Translational Neural Networks, Computer Algorithms Humans
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Interpretable Multi-Scale Deep Learning for RNA Methylation Analysis across Multiple Species.

International journal of molecular sciences Mar 1, 2024
RNA modification plays a crucial role in cellular regulation. However, traditional high-throughput sequencing methods for elucidating their functional mechanisms are time-consuming and labor-intensive, despite extensive research. Moreover, existing m...
RNA Methylation Deep Learning RNA Methylation Protein Processing, Post-Translational
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DeepNphos: A deep-learning architecture for prediction of N-phosphorylation sites.

Computers in biology and medicine Jan 28, 2024
MOTIVATION: Phosphorylation, a prevalent post-translational modification, plays a crucial role in regulating cellular activities. This process encompasses O-phosphorylation (e.g., phosphoserine) and N-phosphorylation (e.g., phospho-lysine (pK), phosp...
Histidine Phosphorylation Arginine Lysine Deep Learning Protein Processing, Post-Translational
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PPSNO: A Feature-Rich SNO Sites Predictor by Stacking Ensemble Strategy from Protein Sequence-Derived Information.

Interdisciplinary sciences, computational life sciences Jan 11, 2024
The protein S-nitrosylation (SNO) is a significant post-translational modification that affects the stability, activity, cellular localization, and function of proteins. Therefore, highly accurate prediction of SNO sites aids in grasping biological f...
Protein Domains Amino Acid Sequence Machine Learning Protein Processing, Post-Translational Proteins
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Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore.

ACS nano Dec 19, 2023
Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several dis...
Nanopores Protein Processing, Post-Translational alpha-Synuclein Peptides Deep Learning
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O-GlcNAcPRED-DL: Prediction of Protein O-GlcNAcylation Sites Based on an Ensemble Model of Deep Learning.

Journal of proteome research Dec 6, 2023
O-linked β--acetylglucosamine (O-GlcNAc) is a post-translational modification (i.e., O-GlcNAcylation) on serine/threonine residues of proteins, regulating a plethora of physiological and pathological events. As a dynamic process, O-GlcNAc functions i...
Proteins N-Acetylglucosaminyltransferases Protein Processing, Post-Translational Acetylglucosamine Humans Deep Learning Mice Animals
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