AIMC Topic: Phosphorylation

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Using support vector machines to identify protein phosphorylation sites in viruses.

Journal of molecular graphics & modelling Dec 24, 2014
Phosphorylation of viral proteins plays important roles in enhancing replication and inhibition of normal host-cell functions. Given its importance in biology, a unique opportunity has arisen to identify viral protein phosphorylation sites. However, ...
Amino Acid Sequence Tyrosine Serine Molecular Sequence Data Viral Proteins Databases, Protein Phosphorylation Phosphoproteins Support Vector Machine Protein Structure, Tertiary Threonine
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Inter-species pathway perturbation prediction via data-driven detection of functional homology.

Bioinformatics (Oxford, England) Aug 22, 2014
MOTIVATION: Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER ...
Bronchi Epithelial Cells Phosphorylation Translational Research, Biomedical Rats Cytokines Software Gene Expression Profiling Signal Transduction Databases, Factual Algorithms Humans Animals Systems Biology Models, Animal Phosphoproteins Cells, Cultured Artificial Intelligence Species Specificity Gene Expression Regulation Oligonucleotide Array Sequence Analysis
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Adaptive learning embedding features to improve the predictive performance of SARS-CoV-2 phosphorylation sites.

Bioinformatics (Oxford, England) Nov 1, 2023
MOTIVATION: The rapid and extensive transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global health emergency, affecting millions of people and causing an immense socioeconomic impact. The id...
Algorithms SARS-CoV-2 Phosphorylation Neural Networks, Computer COVID-19 Humans
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EMBER: multi-label prediction of kinase-substrate phosphorylation events through deep learning.

Bioinformatics (Oxford, England) Apr 12, 2022
MOTIVATION: Kinase-catalyzed phosphorylation of proteins forms the backbone of signal transduction within the cell, enabling the coordination of numerous processes such as the cell cycle, apoptosis, and differentiation. Although on the order of 105 p...
Proteins Phosphorylation Phosphotransferases Phylogeny Deep Learning
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Adapt-Kcr: a novel deep learning framework for accurate prediction of lysine crotonylation sites based on learning embedding features and attention architecture.

Briefings in bioinformatics Mar 10, 2022
Protein lysine crotonylation (Kcr) is an important type of posttranslational modification that is associated with a wide range of biological processes. The identification of Kcr sites is critical to better understanding their functional mechanisms. H...
Neural Networks, Computer Software ROC Curve Reproducibility of Results Algorithms Deep Learning Phosphorylation Computational Biology Protein Processing, Post-Translational Databases, Factual User-Computer Interface Lysine
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Text Mining and Machine Learning Protocol for Extracting Human-Related Protein Phosphorylation Information from PubMed.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
In the modern health care research, protein phosphorylation has gained an enormous attention from the researchers across the globe and requires automated approaches to process a huge volume of data on proteins and their modifications at the cellular ...
Natural Language Processing PubMed Data Mining Proteins Phosphorylation Humans Machine Learning
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A Pretrained ELECTRA Model for Kinase-Specific Phosphorylation Site Prediction.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Phosphorylation plays a vital role in signal transduction and cell cycle. Identifying and understanding phosphorylation through machine-learning methods has a long history. However, existing methods only learn representations of a protein sequence se...
Protein Kinases Machine Learning Phosphorylation
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PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein-protein interaction information.

Bioinformatics (Oxford, England) Dec 11, 2021
MOTIVATION: Phosphorylation is one of the most studied post-translational modifications, which plays a pivotal role in various cellular processes. Recently, deep learning methods have achieved great success in prediction of phosphorylation sites, but...
Proteins Phosphorylation Amino Acid Sequence Neural Networks, Computer Protein Processing, Post-Translational
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Computational Phosphorylation Network Reconstruction: An Update on Methods and Resources.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Most proteins undergo some form of modification after translation, and phosphorylation is one of the most relevant and ubiquitous post-translational modifications. The succession of protein phosphorylation and dephosphorylation catalyzed by protein k...
Phosphoric Monoester Hydrolases Protein Kinases Substrate Specificity Neural Networks, Computer Protein Processing, Post-Translational Phosphorylation Proteome
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DeepPhos: prediction of protein phosphorylation sites with deep learning.

Bioinformatics (Oxford, England) Aug 15, 2019
MOTIVATION: Phosphorylation is the most studied post-translational modification, which is crucial for multiple biological processes. Recently, many efforts have been taken to develop computational predictors for phosphorylation site prediction, but m...
Phosphorylation Neural Networks, Computer Protein Processing, Post-Translational Software Deep Learning
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