Analytics and Model Building Using Multiple File Types
- AugustaTM provides rapid analytics with real-time predictive modelling for use cases in Bioinformatics/health informatics, computational biology:
- MRI/fMRI and other imaging modalities
- Genetics, Proteomics
- Wearables data
- EHR/EMR data
- Real Time Integrative Analytics: combining genomics with clinical and patient monitoring data from your mobile device à towards precision medicine applications in real time
- Small molecule activity prediction
- Patient care quality and program analysis
- Drug discovery and development analysis
- Hospital telemetry and operational data
- Health Insurance fraud detection
Easy Integration into any Business Process
- AugustaTM’s solutions are easy to deploy, saving valuable time and development effort.
- AugustaTM can be seamlessly integrated into existing business processes or embedded directly within user applications.
- Capabilities available for IPython notebooks with Plotly-powered visualizations.
Connect to a Variety of Data Sources
- Through integration with Python, AugustaTM can connect to and read from any data source (g. local storage, databases, cloud storage).
- Modular and customizable pipelines for processing raw phenotypic, imaging, drug, and genomic data sets using any combination of data types.
Parallel and Distributed Computing Enabled
- AugustaTM leverages the performance of the most advanced parallel processors – multi-core CPUs and GPUs – for increased performance during model rebuilds.
- AugustaTM is integrated with Apache Spark for distributed execution.
- Both AugustaTM and SymetryMLTM are deployable on standalone servers, through the Amazon Web Service and Microsoft Azure, with an Apache Spark distributed framework for all steps above.
- Connection to Apache Kafka to retrieve and organize streaming data.
Using data available in the DrugBank Database we generated binding prediction profiles for every known protein target having 5 or more described ligands (607 protein-drug binding models made, 7,149 potential ligands for each, over 4 million drug-ligand activity predictions total)