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MetabolomicsImproving Metabolite Identification with DecoID for Database-Assisted Deconvolution of Metabolomic MS/MS Spectra

Chimeric MS/MS spectra contain fragments from multiple precursor ions and therefore hinder compound identification in metabolomics. Historically, deconvolution of these chimeric spectra has been challenging and relied upon specific experimental methods that introduce variation in the ratios of pr...

2021-04-29 | MTBLS2207 | MetaboLights
MetabolomicseRah: A computational tool integrating spectral deconvolution and alignment with quantification and identification of metabolites in GCMS- based metabolomics
Gas chromatography coupled to mass spectrometry (GC-MS) has been a long- standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex dat...
2016-09-22 | MTBLS321 | MetaboLights
MetabolomicsOptimizing Deconvolution of Chimeric Fragmentation Spectra to reveal molecular structures of complex biological mixtures

Direct infusion mass spectrometry (DI-MS) offers a rapid, high-throughput analysis and, compared to liquid chromatography MS (LC-MS), a different analytical window into the composition of complex biological samples. However, the lack of chromatographic separation in DI-MS results in highly comple...

MTBLS13066 | MetaboLights
MetabolomicsCorrelation-based Deconvolution (CorrDec) to generate high-quality MS2 spectra from data-independent acquisition in multi-sample studies (Urine assay)

Data-independent acquisition mass spectrometry (DIA-MS) is essential for information-rich spectral annotations in untargeted metabolomics. However, the acquired MS2 spectra are highly complex, posing significant annotation challenges. We have developed a correlation-based deconvolution (CorrDec) ...

2020-07-13 | MTBLS816 | MetaboLights
MetabolomicsCorrelation-based Deconvolution (CorrDec) to generate high quality MS2 spectra from data independent acquisition in multi-sample studies (Chemical standards assay)

Data-independent acquisition mass spectrometry (DIA-MS) is essential for information-rich spectral annotations in untargeted metabolomics. However, the acquired MS2 spectra are highly complex, posing significant annotation challenges. We have developed a correlation-based deconvolution (CorrDec) ...

2020-07-13 | MTBLS787 | MetaboLights
TranscriptomicsDeconvolution of ChIP-chip MBF occupancies reveals the temporal recruitment of Rep2 at the MBF-target genes
Deconvolution analysis using Rpb1 ChIP-chip results distinguishes the Cdc10 bindings at the Rpb1-poor loci (promoters) from those at the Rpb1-rich loci (intragenic sequences). Importantly, Res1 binding at the Rpb1-poor loci, but not at the Rpb1-rich loci, are dependent on the Cdc10 function, suggest...
ORGANISM(S): Schizosaccharomyces pombe 
2010-11-26 | E-GEOD-9912 | biostudies-arrayexpress
TranscriptomicsTranscription profiling of human immune cell line mixtures to test deconvolution
Microarray deconvolution is a technique for quantifying the relative abundance of constituent cells in a mixture based on that mixture's microarray signature and the signatures of the purified constituents. Its ability to discriminate related human cells is unknown. Here we test the ability of this...
ORGANISM(S): Homo sapiens 
2009-07-19 | E-GEOD-11058 | biostudies-arrayexpress
ProteomicsProteomics informed deconvolution of 3 cell lines
The project aimed to investigate the possibility to use proteomics data to deconvolute cell line proportions in mixed samples. Samples containing either HEK 293, Caco-2, or A549 cells and mixtures of the three cell lines was analysed using the total protein approach. This was then used for proteomic...
ORGANISM(S): Homo sapiens (Human) 
2023-10-24 | PXD027282 | Pride
Hek 293 A549 Caco-2 
GenomicsDeconvolution
Deconvolution
EGAS00001001219 | EGA
TranscriptomicsMultiple insert size paired-end sequencing for deconvolution of complex transcriptomes
Deep sequencing of transcriptomes allows quantitative and qualitative analysis of many RNA species in a sample, with parallel comparison of expression levels, splicing variants, natural antisense transcripts, RNA editing and transcriptional start and stop sites the ideal goal. By computational model...
ORGANISM(S): Caenorhabditis elegans 
2012-08-31 | E-GEOD-40507 | biostudies-arrayexpress
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