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MetabolomicsCombining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets
Spring wheat (Triticum aestivum L.) was grown in a free-air carbon dioxide (CO2) enrichment (FACE) field experiment. Grain and biomass yield and its components were determined at maturity and the grain metabolome was analysed by gas chromatography-mass spectrometry (GC-MS) for elevated and ambient C...
2012-09-21 | MTBLS21 | MetaboLights
MetabolomicsEvaluation of algorithms for multiple alignment of GCxGC-MS data
In this study, the metabolic difference resulting in H_2 production yield between the C. reinhardtii wild type stem cc406 (wt) and the high H_2-producing strain Stm6Glc4 (mut) at two different time points was compared before (t1) and during (t2) the H_2 production phase.
2013-05-08 | MTBLS37 | MetaboLights
GenomicsA Comparative Analysis of Algorithms for Somatic SNV Detection in Cancer
Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer- normal Illumina exome sequencing of a chronic myeloid le...
EGAS00001000927 | EGA
TranscriptomicsComparative Analysis of RNA-Seq Alignment Algorithms and the RNA-Seq Unified Mapper (RUM).
A critical task in high throughput sequencing is aligning millions of short reads to a reference genome. Alignment is especially complicated for RNA sequencing (RNA-Seq) because of RNA splicing. A number of RNA-Seq algorithms are available, and claim to align reads with high accuracy and efficiency ...
ORGANISM(S): Mus musculus 
2011-08-03 | E-GEOD-26248 | biostudies-arrayexpress
TranscriptomicsComparative analysis of algorithms for integration of copy number and expression data
Chromosomal instability is a hallmark of cancer and genes that display abnormal expression in chromosomally aberrant regions are likely to be key players in tumor progression. Identifying such driver genes from high-throughput data requires computational methods that are capable of integrating data ...
ORGANISM(S): Homo sapiens 
2012-02-10 | E-MEXP-3415 | biostudies-arrayexpress
ProteomicsAPIR: a universal FDR-control framework for boosting peptide identification power by aggregating multiple proteomics database search algorithms
Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences...
ORGANISM(S): Pyrococcus furiosus 
2021-09-21 | PXD028558 | Pride
Pyrococcus furiosus (pfu) Proteomics Complex proteomic standard 
GenomicsA systematic evaluation of pattern discovery algorithms
Pattern discovery algorithms are methods for discovering recurrent, non-random motifs widely used in the analysis of biological sequences. Many algorithms exist but few comparisons have been made amongst them. We systematically profile eight representative methods at multiple parameter settings acro...
ORGANISM(S): Homo sapiens 
2009-11-24 | GSE15370 | GEO
GenomicsAn integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms
An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms
PRJNA514255 | ENA
ProteomicsCombining de novo peptide sequencing algorithms, a synergistic approach to boost both identifications and confidence in bottom-up proteomics
Complex MS-based proteomics datasets are usually analyzed by protein database-searches. While this approach performs considerably well for sequenced organisms, direct inference of peptide sequences from tandem mass spectra, i.e. de novo peptide sequencing, oftentimes is the only way to obtain inform...
ORGANISM(S): Radix auricularia Homo sapiens (Human) Mus musculus (Mouse) Saccharomyces cerevisiae (Baker's yeast) 
2019-09-25 | PXD005280 | Pride
False discovery rate Bottom-up proteomics De novo peptide sequencing Lc-ms/ms 
TranscriptomicsA systematic evaluation of pattern discovery algorithms
Pattern discovery algorithms are methods for discovering recurrent, non-random motifs widely used in the analysis of biological sequences. Many algorithms exist but few comparisons have been made amongst them. We systematically profile eight representative methods at multiple parameter settings acro...
ORGANISM(S): Homo sapiens 
2010-05-19 | E-GEOD-15370 | biostudies-arrayexpress
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