From Raw Expression Data to Informative Biomarkers
Genedata Expressionist® consists of a set of integrated software modules that support the complete biomarker discovery process from study design to data processing, statistical data analysis and result reporting. Each module includes a database as well as a data analysis component and is based on a scalable software architecture capable of handling extremely large data sets and studies, removing computational bottlenecks.
Expressionist modules provide sophisticated statistical tools and data visualization to technology experts, biologists and bio-statisticians alike, fostering collaboration within interdisciplinary research teams. High-level decision support tools, global reporting, and publication functions enable the rapid creation and dissemination of information and knowledge across an organization.
Refiner Array
Captures raw data from a wide range of diverse microarray platforms and processes them according to configurable business rules; Flexible workflow design performs standardized quality control and normalization of thousands of microarrays in minutes; Generates normalized microarray data and process documentation.
Refiner MS
Captures raw data from a wide range of MS instrumentations and processes them according to configurable business rules; Extremely scalable algorithms support a wide range of experimental setups, including LC-MS/MSn, GC-MS, SELDI, SILAC, MRM and Infusion MS.
As part of the Expressionist system, Genedata is developing Refiner Genome for the integrated and whole genome analysis of RNA expression, Gene regulation, DNA methylation, SNP analysis and Copy number variation.
Genedata Analyst
Puts rigorous statistical algorithms and the most powerful visualization tools into the hands of biological experts and biostatisticians alike; Provides integrated and flexible data mining capabilities; Enables researchers to combine data from different experimental platforms; Extremely powerful with data sets consisting of billions of data points; Allows collaboration through session-sharing and graphical analyses workflows; Gives interdisciplinary teams a platform on which to communicate, discuss and interpret the results of biological experiments.