Molecular Profiling Data Analysis & Management

Experimental designs of molecular profiling studies in life sciences are becoming ever more complex with sample sizes continually increasing. Researchers therefore need to integrate, manage, and analyze growing data volumes of escalating complexity.

Genedata Expressionist® helps researchers meet such challenges. Comprehensive and enterprise-level, Genedata Expressionist is a workflow-based software solution for scientific data integration, management, and analysis. Leading pharmaceutical, biotechnology, and agricultural R&D organizations already rely on Genedata Expressionist to integrate and analyze a wide variety of experimental data, such as omics and clinical data. Within a single system designed for high sample throughput, the open and scalable architecture allows Genedata Expressionist to thrive on very large data sets. Delivering a high degree of built-in business logic combined with sophisticated statistical capabilities, the solution enables scientists as well as managers to efficiently solve important scientific questions.

GENEDATA EXPRESSIONIST

for Genomic Profiling
Manages, analyzes, and visualizes massive amounts of genomic, transcriptomic, and epigenomic data from all major technologies, such as next-generation sequencing, high-density microarrays, RT-PCR-, and other genomic technologies.

GENEDATA EXPRESSIONIST

for Mass Spectrometry
Manages, analyzes, and vizualizes massive amounts of proteomic, metabolomic, and lipidomic data from all major technologies, such as label-free LC-MS/GC-MS, labeled experiments (SILAC, iTRAQ, and TMT), MRM, ESI and Infusion MS.

Oncology Research

Easily integrates and automates microarray, PCR, and NGS data analysis from cell lines and clinical tumor samples to help make sense of large amounts of data and provide an improved understanding of carcinogenesis or oncology biomarker identification.

Biotherapeutics Analysis

Automates mass spectrometry data analysis workflows, from any raw data to report in an automated fashion, used for developability analysis, comparability studies of biotherapeutics and biosimilars, and provides real-time monitoring for reliable, compliant, batch quality control.

Other Applications
Highlights of Supported Applications

Genedata Expressionist is an integrated data analysis and data management software solution for a wide array of life science applications. Making research data accessible and comprehensible, the solution helps researchers better understand biomolecules, organism function and disease states, enabling scientific discovery that fights disease and improves health worldwide.

  • Biomarker R&D: Biomarkers are used in many different application areas such as  in clinical research, drug development, and theranostics. Many biomarkers consist of genetic mutations, epigenetic modifications, and gene amplifications or translocations, or combinations thereof.

o    Personalized Medicine: Personalized medicine is a rapidly evolving medical model in healthcare. It involves correlation of biomarkers with a patient’s clinical information to accurately predict susceptibility to developing a disease, the course of the disease, and its response to treatment. Genedata Expressionist provides a sophisticated tool for biomarker research, which answers vital  questions in personalized medicine programs.

o    Toxicogenomics: Toxicogenomics establishes correlations between responses to toxicants and the changes in the molecular profiles of the cells exposed to toxicants. It uses biomarkers to predict toxicity early in drug development. Genedata Expressionist helps to dramatically reduce drug development costs by providing a robust platform for research on the impact of toxins on cells and organisms.

o    Clinical Research: Clinical research uses biomarkers to optimize drug development processes, which enables profound and  early-stage decision making. Clinical research laboratories are applying omics technologies to accurately identify and quantify relevant biomarkers. Genedata Expressionist facilitates the improved understanding of both diseases and treatments.

  • Molecular Diagnostics: The emerging field of molecular diagnostics captures genomic, transcriptomics, epigenomics, as well as proteomic, lipidomic, and metabolomic expression patterns for early disease diagnosis, risk prediction, efficacy monitoring, and prediction of new treatment response. Genedata Expressionist provides the tools for research and clinical development to study various data within a single analysis environment. 
  • Crop Sciences: Crop Science is a diverse discipline that examines the genetic improvement, production and utilization of agronomic and turfgrass crops spanning natural breeding, targeted genetic modifications, and  biofuel crop management. Genedata Expressionist gives crop scientists a  powerful omics data management system.

 

 

Features & Benefits

Genedata Expressionist's workflow data analysis and management system provides a comprehensive, enterprise-level software solution containing all the desired features required of robust, flexible software.

Key Features
Beyond Software

  • Client-server architecture guarantees effortless maintenance and  flexibility
  • Enterprise solution enables end-to-end data and result traceability ensuring standardization and reproducibility
  • Accessibility of valuable data throughout the enterprise: Single platform for enterprise-wide omics data analysis and data management
  • Supports and integrates all major omics technology platforms
  • Shared projects enable collaborative data analysis
  • Carefully selected algorithms and settings, including over 10 years of scientific experience from academic research and industrial collaborations
  • Proven workflow system and intuitive user interface designed for flexibility and ease of use
  • Highly scalable - high-throughput system designed for efficient processing, visualization, and analysis

Benefits
Increased Efficiency

  • Minimizes integration with existing IT environments
  • GxP compliance facilitates FDA submissions
  • Significantly reduces time and cost of data analysis and data management
  • One system for all applications maximizes return on investment and improves experiment efficiency
  • Documented APIs allow for flexible extension with external algorithms and methods
  • Simplifies data integration, independent of source or technology
  • Integrated biological knowledge helps to bridge the gap between statistics and biology
  • Strengthens collaboration within interdisciplinary teams of scientists
  • Enables processing, visualization, and analysis of very large data sets - No limitation on experiment size or number of users