Thermo Fisher Scientific Introduces Software Solutions for LTQ Orbitrap Hybrid Mass Spectrometer
Product News Mar 02, 2007
Thermo Fisher Scientific Inc. has announced the introduction of application-specific software that unleashes the full potential of the Thermo Scientific LTQ Orbitrap, winner of the 2006 R&D 100 award and the Editors Gold Award at PITTCON 2006.
Based on the Thermo Scientific LTQ XL linear ion trap, the LTQ Orbitrap hybrid mass spectrometer can identify proteins with greater confidence than any other mass spectrometry (MS) system.
The high-quality data generated by the LTQ Orbitrap can reduces false-positive rates (FPRs) compared with results obtained from other hybrids. To make the most of this high-quality data, Thermo Scientific software leverages the accurate mass capabilities of the LTQ Orbitrap to achieve the following advantages for proteomics and pharmaceutical users:
• Differential expression analysis: New SIEVE™ differential expression software provides label-free semi-quantitative differential expression analysis of proteins and peptides from the comparison of multiple LC/MS data sets.
BioWorks™ software utilizes mass data from the analysis of iTRAQ™-labeled peptides and the analysis of other labeling experiments such as SILAC™.
• de novo sequence analysis: PEAKS™ software makes full use of the LTQ Orbitrap’s mass for definitive de novo sequencing. Featuring automatic or manual de novo sequencing, PEAKS works seamlessly with Thermo Scientific Xcalibur™ RAW data files or from processed data generated using BioWorks software.
• Metabolite identification: Accurate mass full scan and MS/MS data applied in combination with MetWorks and Mass Frontier software enables confident metabolite identification. MetWorks automated metabolite identification software dramatically simplifies and accelerates the processing and reporting of LC/MSn analyses.
The Mass Frontier mass spectral data tool can offer powerful insight into compound structures with new predictive fragmentation modules. In addition, component detection algorithms and spectral tree extractions allow for the user-defined creation of databases of target compounds.