The Biosurveillance Analytics Resource Directory (BARD): Facilitating the Use of Epidemiological Models for Infectious Disease Surveillance.

Epidemiological modeling for infectious disease is important for disease management and its routine implementation needs to be facilitated through better description of models in an operational context. A standardized model characterization process that allows selection or making manual comparisons of available models and their results is currently lacking. A key need is a universal framework to facilitate model description and understanding of its features. Los Alamos National Laboratory (LANL) has developed a comprehensive framework that can be used to characterize an infectious disease model in an operational context. The framework was developed through a consensus among a panel of subject matter experts. In this paper, we describe the framework, its application to model characterization, and the development of the Biosurveillance Analytics Resource Directory (BARD; http://brd.bsvgateway.org/brd/), to facilitate the rapid selection of operational models for specific infectious/communicable diseases. We offer this framework and associated database to stakeholders of the infectious disease modeling field as a tool for standardizing model description and facilitating the use of epidemiological models.

The collaboratory for MS3D: a new cyberinfrastructure for the structural elucidation of biological macromolecules and their assemblies using mass spectrometry-based approaches.

Modern biomedical research is evolving with the rapid growth of diverse data types, biophysical characterization methods, computational tools and extensive collaboration among researchers spanning various communities and having complementary backgrounds and expertise. Collaborating researchers are increasingly dependent on shared data and tools made available by other investigators with common interests, thus forming communities that transcend the traditional boundaries of the single research laboratory or institution. Barriers, however, remain to the formation of these virtual communities, usually due to the steep learning curve associated with becoming familiar with new tools, or with the difficulties associated with transferring data between tools. Recognizing the need for shared reference data and analysis tools, we are developing an integrated knowledge environment that supports productive interactions among researchers. Here we report on our current collaborative environment, which focuses on bringing together structural biologists working in the area of mass spectrometric based methods for the analysis of tertiary and quaternary macromolecular structures (MS3D) called the Collaboratory for MS3D (C-MS3D). C-MS3D is a Web-portal designed to provide collaborators with a shared work environment that integrates data storage and management with data analysis tools. Files are stored and archived along with pertinent meta data in such a way as to allow file handling to be tracked (data provenance) and data files to be searched using keywords and modification dates. While at this time the portal is designed around a specific application, the shared work environment is a general approach to building collaborative work groups. The goal of this is to not only provide a common data sharing and archiving system, but also to assist in the building of new collaborations and to spur the development of new tools and technologies.