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Find out more at https://genoptics.github.io/
One of the biggest challenges in Life Sciences is the high complexity and volume of the involved bio-data, as well as the lack of appropriate analysis tools that can be employed for the extraction of new knowledge. Visual analytics, namely the simultaneous use of computational data analysis tools with interactive visualizations, is a powerful way of combining algorithms with an intuitive, user-friendly interactive environment in order to extract knowledge from large scale bio-data. GenOptics will allow visual analytics of multi-omics data through a modular system that will integrate multiple interoperable analysis tools into a software platform, leveraging established international technologies and software suites such as Docker and R/Bioconductor.
Objective 1: Integrate computational data analysis processes with a flexible visualization system as a single process through a visual analytics dashboard.
Objective 2: A better exploitation of the accumulated volume of multi-omics data allowing the identification of new biomarkers and new therapeutic targets through targeted clinicobiological studies.
GenOptics will effectively reduce both the time and the total cost in the traditionally complex analysis processes of clinical research and diagnosis. In addition, through the integration of multi-omics bio-data with clinical information, the project will attempt to provide answers to key questions such as the reliable predictive classification of patients based on the identification of new patterns and the emergence of new prognostic indicators. Finally, a thorough assessment and comprehensive evaluation of the GenOptics platform based on the supported functionality and the final results in the four pilot cases, will open the way for its systematic promotion as a credible and accredited commercial solution.
