Professor Daniele Fabris of the University of Maryland Baltimore County is supported by the Analytical and Surface Chemistry program to construct a data-centric collaboration infrastructure, and to develop and evolve it as new data management and analysis capabilities are added. Specifically, the project is focused on data coming from the use of intra-molecular chemical cross-linking followed by mass spectrometric analysis that enables the determination of the three dimensional structure of proteins, RNA, and macro-molecular assemblies (MS3D). This method holds the promise for a high-throughput approach that can work with small amounts of protein and systems that are difficult to crystallize. Such approaches are critically needed to enable the discovery of a very large number of macromolecular structures required to ultimately understand the detailed function of living organisms. The computer infrastructure will incorporate emerging middleware standards for data/metadata management, security, application integration, and collaboration. In the longer term, the project will target a standards-based knowledge synthesis and management capability. This pilot collaboratory will integrate the evaluation of the tools and the measurement of their impact on a newly developing community. The tools developed will be open sourced, and made available as a "collaboration tool kit" for other interested communities. The project involves the initial participation of groups at Sandia National Laboratories, University of California San Francisco, and University of Maryland Baltimore County, as described in a partner project with the same title funded by the "Tools for Collaborations that Involve Data Sharing" program, NIH-PAR-03-134.
The collaborative nature of the proposed activities will ensure not only the broadest possible impact on the emerging MS3D community, but will also constitute a test case and a model for similar implementations in Chemistry, Biology, and Medicine. As an increasing number of complex biomedical problems are tackled by investigators working in more widely distributed, interdisciplinary teams, the need for integrated tools and data sharing ability will be more acute than ever before. Beyond the specific research aims of the project, the proposed activities will also have a direct impact on the education and professional development of the UMBC graduate and undergraduate students who will be directly or indirectly involved with the project.
