Scientific Data Collection and Management

Gryphon has collected data using approaches that range from population surveys to advanced machine learning. Our data management skills include curating scientific data, merging diverse datasets, and developing data standards and approaches to data governance.

CASE STUDIES

01

Curating a Database for Drug Discovery

In a large data management project for National Institute of Allergy and Infectious Diseases (NIAID), Gryphon manages CHEMDB, a chemical and biological database that aids the discovery of potential therapies for AIDS, tuberculosis, and other opportunistic infections. This database holds information curated by Gryphon staff on over 395,000 unique chemical entities with either public information on biological activity against HIV and opportunistic infections associated with AIDS or proprietary data from NIAID screening laboratories. The Gryphon team also maintains the website where the domestic and international research community can access the public data.
02

Managing a Data Processing Center for Influenza Research

The Centers for Excellence in Influenza Research and Surveillance (CEIRS) is a NIAID-funded network of academic laboratories that bring together multi-disciplinary teams of influenza researchers. For the CEIRS Data Processing and Coordinating Center, Gryphon develops structured data standards, designs technical systems, and performs quality assurance on data submissions. We also conduct scientific literature surveillance and facilitate communication with the CEIRS scientific community.
03

Developing an Animal Population Database

For a DTRA surveillance system, Gryphon created a MySQL database based on restructured and augmented data from the USDA Census of Agriculture. Data were ingested and integrated with an automated Java pipeline; missing data and seasonal animal populations were estimated by applying advanced analytic techniques. The resulting database contained 15 million lines of population data on 25 species and 3000 lines on  farm biosecurity and production practices. We used these data to probe the relationship between animal population density and human disease.