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TAPIR / TArgeted Proteomics Information Representation
A fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses.
Computes analytical measures as recommended recently by the Clinical Proteomics Tumor Analysis Consortium Assay Development Working Group for "Tier 2" assays - that is, non-clinical assays sufficient enough to measure changes due to both biological and experimental perturbations. Computed measures include; limit of detection, lower limit of quantification, linearity, carry-over, partial validation of specificity, and upper limit of quantification. MRMPlus streamlines assay development analytical workflow and therefore minimizes error predisposition.
Facilitates processing of the post-acquisition data files and validation of quantification result for scale selected reaction monitoring (SRM). SRMBuilder analyzes large SRM data from multiple file formats, validate the quantification results either automatically or manually, and export the final quantification results. It provides a user friendly graphic interface for manual check and elution time adjustment at transition/compound/sample level. SRMBuilder is a part of the software suite ProteomicsTools.
Improves the capabilities for open-source software development in proteomics, including re-analysis and visualization of data sets. Importantly, mzQuantML ensures that data sets submitted to public repositories contain a trace of how protein values were calculated via peptide intermediates, back to regions in two-dimensional LC-MS space. This data standard can represent quantitative information about regions in two-dimensional retention time versus mass/charge space (called features), peptides, and proteins and protein groups (where there is ambiguity regarding peptide-to-protein inference), and it offers limited support for small molecule (metabolomic) data.
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