for Mass Spectrometry

Genedata Expressionist for Mass Spectrometry

Genedata Expressionist for Mass Spectrometry

Genedata Expressionist® for Mass Spectrometry is a comprehensive, enterprise software solution that manages, analyzes, and visualizes massive amounts of mass spectrometry data. Relied on by researchers worldwide, Genedata Expressionist supports a variety of bioanalytical, proteomics, and metabolomics workflows within a single high-throughput system. Built on an open and flexible client-server architecture, the solution thrives on large experimental data sets from all major instrument vendors and technology platforms and can be easily integrated into existing research IT environments.

Technologies
Selection of Supported Technologies

Genedata Expressionist for Mass Spectrometry is an open and flexible platform that supports all kinds of Mass Spectrometry technologies, like label-free LC-MS/GC-MS, labeled experiments using SILAC, iTRAQ, and TMT, MRM, and Infusion MS. Beyond processing, visualization, and analysis of raw data, the software focuses on data integration, providing a selection of statistical tools advancing our understanding of biological systems and diseases.

Key Features
Beyond Software

  • Comprehensive and interactive visual feedback at every processing step
  • Unmatched noise and background reduction, RT alignment, and m/z calibration
  • Peak detection and quantification, grouping of isotopes and adducts
  • Annotation framework with connection to search engines and databases
  • Rich statistical toolbox covers a wide range of data analysis requirements
  • Proven scalability, 100s of users, 1000s of MS experiments
  • Excellent support and training from scientific and technical experts
  • Integration with in-house databases, proprietary algorithms, and reporting systems through open APIs

Benefits
Increased Efficiency

  • Full, source-independent data integration maximizes value of MS data
  • Unified system guarantees high quality results and data management
  • Sophisticated algorithms enable identification of low abundant biological entities
  • Strengthens collaboration within interdisciplinary teams of scientists
  • Easy and cost-efficient integration with existing IT environments
  • Significantly reduces time and cost of MS data analysis and data management
  • GxP compliance facilitates FDA submissions