Performance evaluation of existing de novo sequencing algorithms.
about
Novor: Real-Time Peptide de Novo Sequencing SoftwareNeutron-encoded signatures enable product ion annotation from tandem mass spectra.Searching for a needle in a stack of needles: challenges in metaproteomics data analysis.Distributed computing and data storage in proteomics: many hands make light work, and a stronger memory.Accurate MALDI-TOF/TOF sequencing of one-bead-one-compound peptide libraries with application to the identification of multiligand protein affinity agents using in situ click chemistry screeningStatistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology.Proteome characterization of the unsequenced psychrophile Pedobacter cryoconitis using 15N metabolic labeling, tandem mass spectrometry, and a new bioinformatic workflow.Parallel proteomics to improve coverage and confidence in the partially annotated Oryctolagus cuniculus mitochondrial proteome.Evaluating the impact of different sequence databases on metaproteome analysis: insights from a lab-assembled microbial mixture.De novo sequencing and homology searching.Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling.Combining results of multiple search engines in proteomics.Molecular tandem repeat strategy for elucidating mechanical properties of high-strength proteins.A ranking-based scoring function for peptide-spectrum matchesTools for exploring the proteomosphere.De novo sequencing of unique sequence tags for discovery of post-translational modifications of proteinsProteomic analysis in the identification of allergenic molecules.Algorithms for the de novo sequencing of peptides from tandem mass spectra.Tools and challenges for diversity-driven proteomics in Brazil.Pan-proteomics, a concept for unifying quantitative proteome measurements when comparing closely-related bacterial strains.Evaluating de novo sequencing in proteomics: already an accurate alternative to database-driven peptide identification?Peptide de novo sequencing of mixture tandem mass spectra.Enhancement of mass spectrometry performance for proteomic analyses using high-field asymmetric waveform ion mobility spectrometry (FAIMS).Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCRDeNovoGUI: an open source graphical user interface for de novo sequencing of tandem mass spectra.PepExplorer: a similarity-driven tool for analyzing de novo sequencing results.Multi-spectra peptide sequencing and its applications to multistage mass spectrometry.Application of de novo sequencing tools to study abiogenic peptide formations by tandem mass spectrometry. The case of homo-peptides from glutamic acid complicated by substitutions of hydrogen by sodium or potassium atoms.Sampling the Arabidopsis transcriptome with massively parallel pyrosequencing.Ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry for peptide de novo amino acid sequencing for a seven-protein mixture by paired single-residue transposed Lys-N and Lys-C digestion.De novo identification and quantification of single amino-acid variants in human brain.Investigation of scrambled ions in tandem mass spectra, part 2. On the influence of the ions on peptide identification.De novo interpretation of tandem mass spectra.Novel proteins from proteomic analysis of the trunk disease fungus Lasiodiplodia theobromae (Botryosphaeriaceae).
P2860
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P2860
Performance evaluation of existing de novo sequencing algorithms.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh-hant
name
Performance evaluation of existing de novo sequencing algorithms.
@en
Performance evaluation of existing de novo sequencing algorithms.
@nl
type
label
Performance evaluation of existing de novo sequencing algorithms.
@en
Performance evaluation of existing de novo sequencing algorithms.
@nl
prefLabel
Performance evaluation of existing de novo sequencing algorithms.
@en
Performance evaluation of existing de novo sequencing algorithms.
@nl
P2093
P356
P1476
Performance evaluation of existing de novo sequencing algorithms.
@en
P2093
Charles Buck
Hamid Mirzaei
Irina Fedulova
Sergey Pevtsov
Xiang Zhang
P304
P356
10.1021/PR060222H
P577
2006-11-01T00:00:00Z