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MetabolomicsDIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics
The extraction of meaningful biological knowledge from high-throughput mass spectrometry data relies on limiting false discoveries to a manageable amount. For targeted approaches in metabolomics a main challenge is the detection of false positive metabolic features in the low signal-to-noise ranges ...
2022-09-05 | MTBLS1108 | MetaboLights
ProteomicsNew mixture models for decoy-free false discovery rate estimation in mass-spectrometry proteomics
We introduce a new decoy-free framework for false discovery rate (FDR) estimation that generalizes present decoy-free approaches (DFAs) while exploiting more search data in a manner similar to target-decoy approaches (TDAs).
ORGANISM(S): Homo sapiens (Human) 
2020-01-10 | PXD020322 | Pride
Proteomics Decoy-free framework False discovery rate Bioinformatics 
MetabolomicsDiscovery and validation of potential serum biomarkers for heart failure by untargeted metabolomics

Detection of biomarkers was extremely important for the early diagnosis, prognosis and therapy optimization of diseases. The purpose of this study was to investigate the differences in serum metabolites between patients with heart failure (HF) and healthy controls (HC), and to diagnose HF qualita...

2025-07-18 | MTBLS9586 | MetaboLights
MetabolomicsFDR-controlled metabolite annotation for high-resolution imaging mass spectrometry imaging MS (LC-MS assay)
High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites directly from tissues, cell cultures, and agar plates with cellular resolution, but is hampered by the lack of bioinformatics for automated metabolite identification. We developed the first bioinformatics fra...
2016-12-05 | MTBLS378 | MetaboLights
MetabolomicsFDR-controlled metabolite annotation for high-resolution imaging mass spectrometry imaging MS (MALDI imaging assay)
High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites directly from tissues, cell cultures, and agar plates with cellular resolution, but is hampered by the lack of bioinformatics for automated metabolite identification. We developed the first bioinformatics fra...
2017-04-10 | MTBLS313 | MetaboLights
MetabolomicsMetabolomics-Driven Discovery of an Introduced Species and Two Malaysian Piper betle L. Variants
The differences in pungency of 'sirih' imply the probable occurrence of several variants of Piper betle L. in Malaysia. However, the metabolite profiles underlying the pungency of the different variants remain a subject of further research. The differences in metabolite profiles of selected M...
2022-03-21 | MTBLS2585 | MetaboLights
MetabolomicsFDR-controlled metabolite annotation for high-resolution imaging mass spectrometry - simulated Imaging MS (Imaging simulation assay)
High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites directly from tissues, cell cultures, and agar plates with cellular resolution, but is hampered by the lack of bioinformatics for automated metabolite identification. We developed the first bioinformatics fra...
2016-12-05 | MTBLS317 | MetaboLights
ProteomicsNovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing
De novo peptide sequencing is a fundamental research area in mass spectrometry (MS) based proteomics. However, those methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate ...
ORGANISM(S): Homo sapiens (Human) 
2024-08-28 | PXD055277 | Pride
False discovery rate De novo peptide sequencing 
UnknownOptimal False Discovery Rate Control for Dependent Data.
Not available
S-EPMC3559028 | biostudies-literature
GenomicsAdaptive local false discovery rate procedures for highly spiky data and their application to RNA sequencing data of yeast SET4 deletion mutants
Adaptive local false discovery rate procedures for highly spiky data and their application to RNA sequencing data of yeast SET4 deletion mutants
PRJNA726542 | ENA
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