{"database":"MassIVE","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://massive-ftp.ucsd.edu/v03/MSV000085371/"]},"type":"primary"},"statusCodeValue":200,"statusCode":"OK"}],"scores":{"citationCount":0,"reanalysisCount":0,"viewCount":0,"searchCount":0},"additional":{"submitter":["Bin Ma"],"full_dataset_link":["https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=7372ec104c204e35bb6044daf5af869a"],"submitter_email":["bin.ma@uwaterloo.ca"],"sample_protocol":[""],"repository":["MassIVE"],"file_size":["174"],"ptm_modification":["n/a"],"data_protocol":[""],"omics_type":["Proteomics"],"instrument_platform":["Orbitrap Fusion (Thermo Scientific instrument model)"],"species":["Homo Sapiens (human)"],"submitter_affiliation":["University of Waterloo"],"pubmed_abstract":["Data dependent acquisition (DDA) and data independent acquisition (DIA) are traditionally separate experimental paradigms in bottom-up proteomics. In this work, we developed a strategy combining the two experimental methods into a single LC-MS/MS run. We call the novel strategy data dependent-independent acquisition proteomics, or DDIA for short. Peptides identified from DDA scans by a conventional and robust DDA identification workflow provide useful information for interrogation of DIA scans. Deep learning based LC-MS/MS property prediction tools, developed previously, can be used repeatedly to produce spectral libraries facilitating DIA scan extraction. A complete DDIA data processing pipeline, including the modules for iRT vs RT calibration curve generation, DIA extraction classifier training, and false discovery rate control, has been developed. Compared to another spectral library-free method, DIA-Umpire, the DDIA method produced a similar number of peptide identifications, but nearly twice as many protein group identifications. The primary advantage of the DDIA method is that it requires minimal information for processing its data."],"pubmed_title":["Data Dependent-Independent Acquisition (DDIA) Proteomics."],"pubmed_authors":["Guan Shenheng S, Taylor Paul P PP, Han Ziwei Z, Moran Michael F MF, Ma Bin B"],"name_synonyms":["Peptidomics."],"description_synonyms":["Experiment."],"pubmed_title_synonyms":["Peptidomics."],"pubmed_abstract_synonyms":["liquid chromatography tandem mass spectroscopy, CDF, CG1849, Procedures, experimental, Peptidomics, False, leg, number, Gene, protein, Model Calibration, protein-containing complex, prevention, LC-MS-MS, l(1)AA33, peptide, Polypeptides, Techniques, method, protein polypeptide chains, POF, peptido, polypeptide chain, Method, Deep, DmelCG1768, method used in an experiment, LC-MSMS, HILDA, Studies, Gene Products, 1, 2, AGAMOUS-like 61, Work Flow, protein aggregate, prevention and control, Technique, DiA, Hierarchical, methods, F, LCMSMS, l(2)k07135, peptides, reference sample, teaching, experimental section, Runt, stubby, proteins, procedures, DIASP, SCAN, free, DIA, Dia, Study, preventive measures, 4-(4-dihexadecylaminostyryl)N-methylpyridium iodide, set, data processing, Methodological Studies, method used in an experiment., l(1)B2/13.1, RUN, Run, grupos, curriculum, 38E.16, peptidos, DIA2, Model, LB5, Controlled, LC-MS2, Controlling, l(1)LB9, preventive therapy, grupo, protein complex, Desmoplastic astrocytoma of infancy, Learning, Proteins, LC-MS/MS, DmelCG1849, CG1768, Procedure, Rnt, DRF2, Peptide, AA33, group, lLB5, shortened, polypeptide, ms(2)04138, Desmoplastic infantile astrocytoma, LC/MS/MS, Workflows, native protein, natural protein, Model Calibrations, MLPLI, Protein, techniques, Dias, Library, Sensor, training, ensemble, prophylaxis, POF2, F27C12_24, F27C12.24, Rest, l(1)19Ea, Methodological, Methodological Study, experimental procedures, plan specification, Protein Gene Products, P235, Gene Proteins, data analysis, control, liquid chromatography-tandem mass spectroscopy, Calibration, Sensor Calibration, cardinality, DIANA, Calibrations, Sensor Calibrations, liquid chromatography tandem mass spectrometry, Peptid, Polypeptide, short, groupe, Work Flows, methodology, Hierarchical Learning, Gruppe"],"citation_count":["0"],"additional_accession":["PXD018973"]},"is_claimable":false,"name":"Data Dependent-Independent Acquisition (DDIA) Proteomics","description":"data for DDIA (Data Dependent-Independent Acquisition) experiment","dates":{"publication":"Mon May 04 06:38:00 BST 2020"},"accession":"MSV000085371","cross_references":{"pubmed":["32539411"],"TAXONOMY":["9606"]}}