GutenTag: high-throughput sequence tagging via an empirically derived fragmentation model.
about
Monte carlo simulation-based algorithms for analysis of shotgun proteomic dataDeNovoID: a web-based tool for identifying peptides from sequence and mass tags deduced from de novo peptide sequencing by mass spectroscopy.Transformation and other factors of the peptide mass spectrometry pairwise peak-list comparison process.A comprehensive and scalable database search system for metaproteomicsA Heuristic method for assigning a false-discovery rate for protein identifications from Mascot database search resultsComputational methods for protein identification from mass spectrometry dataAnalyzing proteomes and protein function using graphical comparative analysis of tandem mass spectrometry results.Mass spectrometry-based proteomics and its application to studies of Porphyromonas gingivalis invasion and pathogenicity.Modeling peptide fragmentation with dynamic Bayesian networks for peptide identificationCurrent algorithmic solutions for peptide-based proteomics data generation and identificationProteomics and the analysis of proteomic data: 2013 overview of current protein-profiling technologies.Bioinformatics in mass spectrometry data analysis for proteomics studies.Proteomics and the analysis of proteomic data: an overview of current protein-profiling technologiesMicrowave-assisted enzyme-catalyzed reactions in various solvent systems.SeMoP: a new computational strategy for the unrestricted search for modified peptides using LC-MS/MS data.Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides.Fragmentation characteristics of collision-induced dissociation in MALDI TOF/TOF mass spectrometry.Tandem mass spectrometry data quality assessment by self-convolution.PARPST: a PARallel algorithm to find peptide sequence tags.Separating the wheat from the chaff: unbiased filtering of background tandem mass spectra improves protein identification.Efficient discovery of abundant post-translational modifications and spectral pairs using peptide mass and retention time differences.MassMatrix: a database search program for rapid characterization of proteins and peptides from tandem mass spectrometry data.Integrated platform for manual and high-throughput statistical validation of tandem mass spectra.A hybrid, de novo based, genome-wide database search approach applied to the sea urchin neuropeptidomeA high-throughput de novo sequencing approach for shotgun proteomics using high-resolution tandem mass spectrometry.Proteomic analyses using Grifola frondosa metalloendoprotease Lys-N.Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences.DirecTag: accurate sequence tags from peptide MS/MS through statistical scoringAn empirical strategy for characterizing bacterial proteomes across species in the absence of genomic sequences.Discussion on common data analysis strategies used in MS-based proteomics.DeltAMT: a statistical algorithm for fast detection of protein modifications from LC-MS/MS data.Identification of alternative splice variants in Aspergillus flavus through comparison of multiple tandem MS search algorithms.ProbPS: a new model for peak selection based on quantifying the dependence of the existence of derivative peaks on primary ion intensity.Two-phase Filtering Strategy for Efficient Peptide Identification from Mass SpectrometryIdentifying proteomic LC-MS/MS data sets with Bumbershoot and IDPickerImproved molecular weight-based processing of intact proteins for interrogation by quadrupole-enhanced FT MS/MS.A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.Exhaustive database searching for amino acid mutations in proteomes.Recent developments in quantitative proteomics.Mass spectrometry-based protein identification by integrating de novo sequencing with database searching
P2860
Q24648679-27326AB7-E764-439E-8831-62DF7B67F8AAQ24813129-B2727366-F707-42F5-841D-F938E397C0AAQ25257201-9D67AE89-8716-4DB8-BA5F-3AF3179F911DQ27098545-EDCE32A2-C276-47FB-8399-959EDA75D7D2Q28306772-EB32E99C-2AD9-42E9-AB69-E2030601443CQ30000994-0D5FC6B1-ADED-413B-8896-565A3D849509Q30354439-FF6046C9-85BB-4CD2-8ADC-E1CE0EC21E18Q30439892-1827830A-12EF-48CC-A438-E7D0A7C7CE3DQ30490288-69B4F265-63BB-42D4-9353-E5A47167A73DQ30577060-0D9C0593-A2D3-4ED6-948B-65A0DD0198E2Q30601945-77931032-8638-4FEB-A4CD-E4B1910C8C38Q30992462-BD0CC9AF-6D23-4F31-B9CC-1CC76A422723Q31153300-ED2B0221-0F14-4D02-8F84-0CEA8565E1ACQ31156521-D1A1ACB6-B8C0-437D-BA8C-E95EDCE39882Q31169956-D937CACF-11B6-4AA6-A18A-5AC250826F89Q33229418-2C37548A-0F3D-482E-BD79-2DFA59CC14B9Q33279137-AC1BC1E6-9CD5-4103-8A68-3DCE4CAEE982Q33299620-1AD9836F-AF8C-4518-A79B-A08970F82F7DQ33331980-A8F08D16-7286-4502-BB36-A93ECFEA7C50Q33344186-7D980B71-8445-4A09-8E89-C1CC1426C541Q33407877-C822C94A-1F13-47AB-9E94-7F614DE2A585Q33411375-0159BCD9-772F-4A1F-A781-F44C1BFD36B0Q33467463-E1247796-5789-4B6C-B349-4FA8DCD30825Q33517721-F2F9EB5F-DB44-4C30-A979-C7000939414AQ33537380-2C79884E-8E0B-4E80-8A0F-40FA2E4E81F5Q33559849-8F2C8304-FF19-41D4-97A8-77DDBA193464Q33607513-AE946523-550F-49E5-B1D2-E7F39D856E9CQ33607530-0DF0D42D-E1F6-4BD7-8346-7782309C5F38Q33754388-742DB99D-F63E-45A4-9B1A-C84FC19E931CQ33795085-D3392417-A912-48AE-9B4D-73C0E9234F75Q33820553-8BF66955-F071-4AC3-809E-165C29609110Q33957242-B67DB4A1-D322-46C6-BC25-D4B29AFAC538Q33995236-184343B1-B006-4A5B-97AE-81E65600972CQ34066467-7D381E09-E2F2-425E-92D3-0F04400A1D2EQ34184101-298F8DDE-167C-40DC-81F3-239E81ACB265Q34195149-5FEB1F36-64E7-4E05-861B-BAF03BD22951Q34207316-4A2E42FE-F7AB-4116-B29F-157AA34851FEQ34267246-700A23A3-0520-4FAC-9268-53B208724D1AQ34307294-D56737BE-4C23-4147-A145-90B998D7D2DFQ34569785-A8C976CC-D2B7-4F32-A47B-A5731B7DC040
P2860
GutenTag: high-throughput sequence tagging via an empirically derived fragmentation model.
description
2003 nî lūn-bûn
@nan
2003年の論文
@ja
2003年論文
@yue
2003年論文
@zh-hant
2003年論文
@zh-hk
2003年論文
@zh-mo
2003年論文
@zh-tw
2003年论文
@wuu
2003年论文
@zh
2003年论文
@zh-cn
name
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@en
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@nl
type
label
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@en
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@nl
prefLabel
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@en
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@nl
P2860
P356
P1433
P1476
GutenTag: high-throughput sequ ...... y derived fragmentation model.
@en
P2093
Anita Saraf
John R Yates
P2860
P304
P356
10.1021/AC0347462
P407
P50
P577
2003-12-01T00:00:00Z