Genedata Expressionist for MS processes large experimental data sets of GC- and LC-MS (/MS), labeled and unlabeled – regardless of data formats.
Each technology workflow requires specific pre-processing steps to create comparable experiments and to enable statistical analysis across samples.
Genedata Expressionist for MS rapidly automates and standardizes such pre-processing and performs integrated statistical analysis of extremely large and diverse biological data sets.
Genedata Expressionist for MS also features advanced data mining and visualizations, complemented by statistical applications including t-Test, ANOVA, Linear Models, Principal Components Analysis (PCA), and Partial Least Square (PLS) analysis.
Takeda said it will capitalize on the latest advancements in multi-vendor MS data integration, support for untargeted proteomics and metabolomics, and targeted Multiple Reaction Monitoring (MRM).
Genedata CEO Othmar Pfannes said the company has seen an increase in applications for discovering protein and metabolite biomarkers based on MS technologies, in particular for personalized medicine and drug safety studies.
"Genedata Expressionist supports a wide range of applications and enables a highly efficient drug discovery process," Pfannes said.