In 2016, The Answer ALS Team began to design an unprecedented system to effectively and efficiently combine/integrate our community data. Ensuring inclusions of stakeholders will allow us to integrate the data not only from Answer ALS but also with other research data, clinical information, participant input, participant health record information, family medical histories, environmental data, medical sensor data (wearables) and more.
Through Answer ALS and other community partner initiatives, as increasingly large amounts of genomic and other participant/family information become available, more efficient, sensitive, and specific analyses are critical. Answer ALS and our community partners will ensure that our ability to collect, process, and securely store information does not outpace the ability of our researchers to analyze the data. Answer ALS, will leverage state-of-the-art big-data and machine learning technologies to analyze information in ways never before imagined.
Answer ALS, working with our community partners, will leverage state-of-the-art big-data and machine learning technologies to analyze information in ways never before imagined.
Answer ALS is working with our community partners, and in the larger research ecosystem, to design and execute an unprecedented system to effectively and efficiently combine/integrate our community data – leveraging existing capabilities to the extent practicable and connecting the wealth of information that already exists from basic molecular research, clinical insights, environmental data and others.
In an effort to make our data analysis transparent, reproducible and accessible to the scientific community we will be releasing our computational workflows publicly. To accomplish this goal, we’ve adopted the Galaxy platform, which allows both skilled bioinformaticians as well as experimental biologists to view and run computational workflows using a graphical interface. Moreover, to boost our capabilities for large-scale analysis, our Galaxy instance operates on the cloud computing platform Microsoft Azure, allowing us to process, analyze and integrate new data as they are generated by the consortium.
Answer ALS data will serve as the foundation for new clinical trials, new ways to subgroup participant to better discover successful drugs, to find drug responsive biomarkers or diagnostics. Answer ALS will enable researchers to share these new insights, techniques, processes and ideas. The connections and patterns that emerge will suggest test able hypotheses and new conceptual syntheses for researchers, implicate mechanisms of disease for researchers and clinicians, and enable more novel approaches.