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Credential Features
A powerful platform to discriminate biological features from the various noise sources prevalent in untargeted metabolomic data. The process is experimentally straightforward and can be easily implemented in any metabolomic laboratory. Feature credentialing reliably removes artifactual features such as those arising from chemical and informatic noise, thereby resulting in a valuable list of features of biological origin. These credentialed features address many of the drawbacks associated with feature counting in comparing method performance on the basis of metabolome coverage. As such, counting credentialed features can be used in the development and optimization of untargeted metabolomic approaches as demonstrated by the reoptimization of XCMS parameters. Credentialing features is also an effective data reduction strategy for untargeted metabolomic results such that a smaller number of peaks can be targeted for MS/MS analysis.
IPO / Isotopologue Parameter Optimization
Optimizes XCMS peak picking parameters by using natural, stable 13C isotopic peaks to calculate a peak picking score. Retention time correction is optimized by minimizing relative retention time differences within peak groups. Grouping parameters are optimized by maximizing the number of peak groups that show one peak from each injection of a pooled sample. IPO was successfully applied to data derived from liquid chromatography coupled to high resolution mass spectrometry from three studies with different sample types and different chromatographic methods and devices.
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MaConDa / Mass spectrometry Contaminant Database
Gathers information about mass spectrometry (MS) contaminants. MaConDa is a manually curated database which compiles theoretical and/or experimental data for over 200 records extracted from scientific literature and various contributors. Each entry is recorded with several databases identifiers to facilitate cross-referencing and data can be downloaded in a wide range of formats. It aims to help in processing data for metabolomics and bioanalytical chemistry researchers.
MS-MS Fragment Viewer
Provides a visualization tool of tandem mass-spectrometry (MS-MS) Fragment. MS-MS Fragment Viewer is a database for metabolomics which consists of the FT-MS, IT- and FT-MS/MS spectral data with predicted structures of fragment ion observed in LC-FT/ICR-MS analysis. This database also includes the photodiode array detection spectra of these compounds which provide additional information of structure. This resource can help to assign same compounds observed in mass spectra, and to annotate a structure of unknown compound whose spectra are not provided enough in public.
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