Product Overview
GeneBrain® is a Digital Infuzion data analytics solution that allows researchers and clinicians to gain ‘at a glance’ insights into complex biological data. 3-dimensional visualizations enable biological discoveries and insights intuitively while transparently basing them in cutting edge mathematics and our patented self-optimizing learning machines.
Enhance clinical studies, basic and translational research, and biosurveillance
Digital Infuzion developed GeneBrain® to conduct data analysis in a simple, intuitive and visually appealing manner. GeneBrain® has been successfully applied to clinical studies including vaccine efficacy, research data such as gene expression and proteomics, biosurveillance and the integration of data from multiple technology platforms.
We leveraged our expertise in computer science, big data analytics, artificial intelligence and biology into a quicker, more efficient and higher yielding analytics system for our clients.
Benefits
- Ability to visualize data enabling detection of outliers or lack of uniformity in enrolled patient populations
- Identification of which data features or groupings of features out of thousands are predictive or characteristic
- Integration of multiple data pipelines for effective, unified analysis
- Query capability to find matching patterns whether actual or hypothetical
- Formulate and refine hypotheses about data in silico saving research costs
- Put data exploration into the hands of non-mathematicians to explore high dimensional data and full repositories for discovery, surveillance and hypothesis testing using visualization tools
Key Features and Applications
Ease of Understanding
Harness the power of advanced mathematics through intuitive 3-dimensional visualizations to understand trends, natural data groupings, and important characteristics that improve data interpretation.
Enhanced Prospective Analysis
Identify groups of predictive characteristics, not just single biomarkers, and include multiple data types.
Test and refine hypotheses in silico to reduce actual laboratory and clinical costs.