Sort   by:  
 Page size 
MetabolomicsIntegrated Analysis of Gut Microbiota, Serum Metabolomics, and Proteomics Reveals Novel Associations With Clinical Symptoms in Patients With Cerebral Infarction
Cerebral infarction (CI) is a major cause of adult disability and mortality worldwide. Mounting evidence supports the critical role of the gut–brain axis in cerebrovascular disease progression. This study aimed to characterize the alterations in gut microbiota, serum metabolome, and serum proteome i...
2026-05-08 | MTBLS14356 | MetaboLights
UnknownPerformance Characteristics of Zeno Trap Scanning DIA for Sensitive and Quantitative Proteomics at High Throughput.
Not available
S-EPMC12809002 | biostudies-literature
GenomicsBenchmarking DIA-type Proteomics Using Large-Scale Inter-Patient Heterogeneity Dataset
Benchmarking Proteomics Quantitation in DIA-type data using real patient material to create a benchmark dataset comprising inter-patient heterogeneity
EGAS00001005589 | EGA
UnknownDIA-BERT: pre-trained end-to-end transformer models for enhanced DIA proteomics data analysis.
Not available
S-EPMC11997033 | biostudies-literature
UnknownAnalysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform.
Not available
S-EPMC10338508 | biostudies-literature
ProteomicsProtein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics
Mass spectrometry-based proteomics is challenged by the presence of contaminant background signals. In particular, protein contaminants from reagents and sample handling are often abundant and almost impossible to avoid, reducing the sensitivity, specificity and reproducibility of protein identifica...
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) Mus Musculus (ncbitaxon:10090) 
2022-01-21 | MSV000088714 | MassIVE
GenomicsBenchmark Dataset DIA Clinical Proteomics LymphNodes E.coli
Real patient variability Benchmark Dataset for Optimization of DIA data analysis workflows
EGAD00010002223 | EGA
Proteomics,MultiomicsDIA-Umpire: comprehensive computational framework for data independent acquisition proteomics
This dataset consists of 44 raw MS files, comprising 27 DIA (SWATH) and 15 DDA runs on a TripleTOF 5600 and of two raw mass spectrometry files acquired on a Q Exactive. The composition of the dataset is described in the manuscript by Tsou et al., titled: "DIA-Umpire: comprehensive computational fra...
ORGANISM(S): Escherichia Coli (ncbitaxon:562) Homo Sapiens (ncbitaxon:9606) 
2017-04-27 | MSV000081023 | MassIVE
UnknownLocalization of Organelle Proteins Using Data-Independent Acquisition (DIA-LOP).
Not available
S-EPMC12455123 | biostudies-literature
UnknownComparative Analyses of Data Independent Acquisition Mass Spectrometric Approaches: DIA, WiSIM-DIA, and Untargeted DIA.
Not available
S-EPMC5817406 | biostudies-literature
Sort   by:  
 Page size