Technologies


Adaptive Analysis Framework

Reference#: P01877


This technology, the Adaptive Analysis Framework (AAF) is a novel design and maintenance plan for large databases associated with biological and medical research problems or clinical assessments that make use of large scale data sources within multiple and separate laboratory facilities. The framework manages and assists the collection, analysis and storage of immense and distributed sets of data and helps establish protocols for new research projects.

While the application focuses on biological agent identification, the technology can also apply to other biological/medical research problems and/or clinical assessments. AAF is a defined process by which other experiments and domains may be modeled and supporting components generated to customize.

AAF consists of the data model, data entry, data retrieval, and data analysis components. The data entry component allows for web-based entry into a central or distributed data repository. This repository is arbitrary; it only need support the JDBC or ODBC interfaces. The data retrieval component may be implemented as a web-based component or a desktop application. Data analysis consists of either implementing relevant techniques within the retrieval component or integrating with third-party applications. The key to the AAF is the data model that drives the specific implementations of the other components.

The current AAF implementation consists of an ER data model of the elements of a microarray experiment. For example, the model includes representations of items such as experiment stages, target organisms and chip microarray structure. The data entry consists of a web page that allows the collection of experimental data from various laboratories across the nation. The web page data entry forms and underlying software are designed to automate the addition of the data into the repository. Finally, the system has the ability to retrieve and analyze the experimental results using platform-independent, Java-based retrieval and analysis components that have the ability to interoperate with Microsoft Excel and Matlab.

CONTACT:
Dr. G. R. Jacobovitz
Phone: (443) 778-9899
ott-techmanager3@jhuapl.edu