Computational prediction of eukaryotic phosphorylation sites.
about
Systematic analysis and prediction of pupylation sites in prokaryotic proteinsComputational phosphoproteomics: from identification to localizationDynamic Alterations to α-Actinin Accompanying Sarcomere Disassembly and Reassembly during Cardiomyocyte MitosisResolution of protein structure by mass spectrometry.Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data.Protein structure as a means to triage proposed PTM sites.Parallel in vivo DNA assembly by recombination: experimental demonstration and theoretical approachesImproving the performance of protein kinase identification via high dimensional protein-protein interactions and substrate structure data.A Synthetic Kinome Microarray Data GeneratorExploiting holistic approaches to model specificity in protein phosphorylationIntegrating phosphoproteomics in systems biology.CPhos: a program to calculate and visualize evolutionarily conserved functional phosphorylation sites.In-situ enrichment of phosphopeptides on MALDI plates modified by ambient ion landing.Prediction of protein phosphorylation sites by using the composition of k-spaced amino acid pairs.Testing whether metazoan tyrosine loss was driven by selection against promiscuous phosphorylation.PKIS: computational identification of protein kinases for experimentally discovered protein phosphorylation sitesGlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.jEcho: an evolved weight vector to characterize the protein's post-translational modification motifs.A grammar inference approach for predicting kinase specific phosphorylation sites.Computational prediction of protein-protein interactions.jEcho: an Evolved weight vector to CHaracterize the protein's posttranslational modification mOtifs.Functional Diversification after Gene Duplication: Paralog Specific Regions of Structural Disorder and Phosphorylation in p53, p63, and p73Computational Analysis of the Predicted Evolutionary Conservation of Human Phosphorylation Sites.Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thalianaDephosSite: a machine learning approach for discovering phosphotase-specific dephosphorylation sites.RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest.Prioritizing functional phosphorylation sites based on multiple feature integration.PredPhos: an ensemble framework for structure-based prediction of phosphorylation sitesProbabilistic Prediction of Protein Phosphorylation Sites Using Classification Relevance Units Machines.Mitotic phosphorylation of eukaryotic initiation factor 4G1 (eIF4G1) at Ser1232 by Cdk1:cyclin B inhibits eIF4A helicase complex binding with RNA.PSEA: Kinase-specific prediction and analysis of human phosphorylation substrates.Understanding and applying tyrosine biochemical diversity.Progress and challenges in predicting protein methylation sites.PhosD: inferring kinase-substrate interactions based on protein domains.Revisiting protein kinase-substrate interactions: Toward therapeutic development.Integration of conventional quantitative and phospho-proteomics reveals new elements in activated Jurkat T-cell receptor pathway maintenance.Predicting Post-Translational Modifications from Local Sequence Fragments Using Machine Learning Algorithms: Overview and Best Practices.Prediction of Protein Phosphorylation Sites by Integrating Secondary Structure Information and Other One-Dimensional Structural Properties.Computational phosphorylation site prediction in plants using random forests and organism-specific instance weights.An ensemble method approach to investigate kinase-specific phosphorylation sites.
P2860
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P2860
Computational prediction of eukaryotic phosphorylation sites.
description
article científic
@ca
article scientifique
@fr
articol științific
@ro
articolo scientifico
@it
artigo científico
@gl
artigo científico
@pt
artigo científico
@pt-br
artikel ilmiah
@id
artikull shkencor
@sq
artículo científico
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name
Computational prediction of eukaryotic phosphorylation sites.
@en
Computational prediction of eukaryotic phosphorylation sites.
@nl
type
label
Computational prediction of eukaryotic phosphorylation sites.
@en
Computational prediction of eukaryotic phosphorylation sites.
@nl
prefLabel
Computational prediction of eukaryotic phosphorylation sites.
@en
Computational prediction of eukaryotic phosphorylation sites.
@nl
P2860
P356
P1433
P1476
Computational prediction of eukaryotic phosphorylation sites.
@en
P2093
Brett Trost
P2860
P304
P356
10.1093/BIOINFORMATICS/BTR525
P407
P577
2011-09-16T00:00:00Z