Thermo Develops Advanced Protein Identification and Quantitation Software
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Thermo Electron Corporation has extended its protein identification and quantitation software package with the BioWorks™ 3.3. Featuring unique PepQuan capabilities, BioWorks 3.3 enables automated quantitative analysis of iTRAQ™, SILAC™ and ICAT® labeled samples, as well as label-free quantitation techniques.
Additionally, a unified Search Results File (SRF) is designed to simplify and accelerate the review and transfer of results by allowing all of the information to be stored in a single file.
These capabilities are detailed in a brochure, which is available online at free of cost.
With pre-search and post-search filters, BioWorks 3.3 removes unwanted spectra from the search resulting in faster search times, allowing users to focus only on the proteins of interest.
Spectra and tables can be transferred to Microsoft® Office documents, while the Protein Report feature enables printing of data directly from search results or the creation of PDF files.
BioWorks 3.3 features the SEQUEST® protein search algorithm, which automatically identifies proteins by comparing experimental tandem mass spectrometry (MS/MS) data with standard protein and DNA databases.
It can analyze a single spectrum or an entire LC/MS/MS data set containing spectra from a mixture of proteins.
The proprietary "cross-correlation" identification algorithm within SEQUEST is designed to extract information and correctly identify proteins even at low concentrations.
Accurate mass capability is also incorporated in the BioWorks 3.3 software package to enable SEQUEST searching on data acquired using Thermo’s hybrid mass spectrometers.
The software package can also process datasets acquired using vMALDI™ equipped LTQ XL™ systems Featuring enhanced SEQUEST Queue and Batch Search capabilities, users will also be able to launch searches on Mascot server from Bioworks 3.3 and compare SEQUEST and Mascot search results.
The Bioworks 3.3 provides tools for automated analysis of iTRAQ labeled samples, as well as SILAC and metabolic labeling experiments.
