Semi-supervised learning for peptide identification from shotgun proteomics datasets.
about
Conic sampling: an efficient method for solving linear and quadratic programming by randomly linking constraints within the interiorEvolutionarily repurposed networks reveal the well-known antifungal drug thiabendazole to be a novel vascular disrupting agentProteomics reveals novel Drosophila seminal fluid proteins transferred at matingThe functional interactome landscape of the human histone deacetylase familyUnambiguous phosphosite localization using electron-transfer/higher-energy collision dissociation (EThcD)mspire: mass spectrometry proteomics in RubyA CRISPR screen defines a signal peptide processing pathway required by flavivirusesImproved False Discovery Rate Estimation Procedure for Shotgun ProteomicsThe EARP Complex and Its Interactor EIPR-1 Are Required for Cargo Sorting to Dense-Core VesiclesExtraordinary Diversity of Immune Response Proteins among Sea Urchins: Nickel-Isolated Sp185/333 Proteins Show Broad Variations in Size and ChargeThe molecular architecture of the Dam1 kinetochore complex is defined by cross-linking based structural modelling.Proteome wide purification and identification of O-GlcNAc-modified proteins using click chemistry and mass spectrometryKinetochore biorientation in Saccharomyces cerevisiae requires a tightly folded conformation of the Ndc80 complex.Chasing Phosphoarginine Proteins: Development of a Selective Enrichment Method Using a Phosphatase TrapDe novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificityArginine phosphorylation marks proteins for degradation by a Clp proteaseCardiovascular proteomics in the era of big data: experimental and computational advancesMetabolic-stress-induced rearrangement of the 14-3-3ζ interactome promotes autophagy via a ULK1- and AMPK-regulated 14-3-3ζ interaction with phosphorylated Atg9OpenMS: a flexible open-source software platform for mass spectrometry data analysisLearning from decoys to improve the sensitivity and specificity of proteomics database search resultsCRISPR-Cas9-based knockout of the prion protein and its effect on the proteomeTriacylglycerol Storage in Lipid Droplets in Procyclic Trypanosoma bruceiCustom 4-Plex DiLeu Isobaric Labels Enable Relative Quantification of Urinary Proteins in Men with Lower Urinary Tract Symptoms (LUTS)Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic AnalysisIn-Depth Characterization of Sheep (Ovis aries) Milk Whey Proteome and Comparison with Cow (Bos taurus)Prion Protein Deficiency Causes Diverse Proteome Shifts in Cell Models That Escape Detection in Brain TissueComprehensive Annotation of the Parastagonospora nodorum Reference Genome Using Next-Generation Genomics, Transcriptomics and ProteogenomicsPerformance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap InstrumentQuantitative and Selective Analysis of Feline Growth Related Proteins Using Parallel Reaction Monitoring High Resolution Mass SpectrometryProXL (Protein Cross-Linking Database): A Platform for Analysis, Visualization, and Sharing of Protein Cross-Linking Mass Spectrometry DataIlluminating structural proteins in viral "dark matter" with metaproteomicsProcessing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipelineOpen source libraries and frameworks for mass spectrometry based proteomics: a developer's perspectiveA mass spectrometry proteomics data management platformGetting started in computational mass spectrometry-based proteomicsProteomic Analysis of Liver Proteins in a Rat Model of Chronic Restraint Stress-Induced DepressionSemi-supervised prediction of protein subcellular localization using abstraction augmented Markov modelsNovor: Real-Time Peptide de Novo Sequencing SoftwareA draft map of the human proteomeIdentification of GAPDH on the surface of Plasmodium sporozoites as a new candidate for targeting malaria liver invasion
P2860
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P2860
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年学术文章
@wuu
2007年学术文章
@zh-cn
2007年学术文章
@zh-hans
2007年学术文章
@zh-my
2007年学术文章
@zh-sg
2007年學術文章
@yue
2007年學術文章
@zh
2007年學術文章
@zh-hant
name
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@en
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@nl
type
label
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@en
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@nl
prefLabel
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@en
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@nl
P50
P356
P1433
P1476
Semi-supervised learning for peptide identification from shotgun proteomics datasets.
@en
P2093
Jesse D Canterbury
P2888
P304
P356
10.1038/NMETH1113
P577
2007-10-21T00:00:00Z
P5875
P6179
1029861497