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ProMass Deconvolution 2.5
ProMass Deconvolution 2.5 is an automated biomolecule deconvolution and reporting software package that is used to process ESI/LC/MS data or single ESI mass spectra acquired with the Thermo Scientific Xcalibur data system. ProMass is ideal for the analysis of intact proteins and oligonucleotides and is optimized for high-throughput applications.

You can now also order additional proteomics resources, or learn about other mass spectrometry or proteomics solutions.

ProMass produces artifact-free deconvoluted ESI mass spectra of biomolecules. ProMass uses a novel deconvolution algorithm known as ZNova™ that produces artifact-free deconvoluted mass spectra. ZNova can be used to process data from a wide variety of biomolecules including proteins, oligonucleotides, peptides, etc. Unlike many other deconvolution algorithms, ZNova can accomodate low charge state spectra and data of low signal-to-noise ratio.

ProMass automatically processes multiple files from an Xcalibur sample sequence. ProMass processing can be initiated through the Xcalibur Sequence Setup view, which allows the user to run a list of samples and have ProMass process them automatically.

ProMass provides web-based results including chromatograms, color-coded summary and tabular results. ProMass reports results automatically in an easy-to-use and interactive format viewable from any web browser. A top-level summary page summarizes the results from multiple runs and displays them on a single hyperlinked page allowing the user to navigate results quickly.

ProMass automatically finds and reports target masses of proteins, peptides, and oligonucleotides. Target mass features allow the user to search for multiple target masses from LC/MS data automatically. The target mass features include results color coding, allowing the user to quickly determine which samples that may require immediate attention.

ProMass Deconvolution 2.5 includes a new viewer that allows the user to expand the spectrum, get additional information and to export the data.