Database-driven software for biological NMR analysis

University Of Connecticut Sch Of Med/Dnt, Farmington CT

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): NMR spectroscopy on biological macromolecules generates vast amounts of data and requires intricate knowledge of the molecular system under study for successful analysis of the acquired data. The size and complexity of the molecular systems have grown to the point where database integration is essential to improve the productivity of NMR studies, maximize the efficiency of NMR data analyses, and guarantee the validity of such analyses. In addition, there exist a large number of valuable NMR analysis tools, intricately interdependent in the information they provide and require. Due to this interdependence, a conceptual data model for both raw and analyzed NMR data is required to provide a database system capable of format conversion among the codependent software. In the absence of such a model, much NMR data is considered too complicated to be thoroughly treated and is effectively discarded. Until such a data model is developed and distributed, along with software to support it, the bulk of the information provided by biological NMR spectroscopy will continue to be lost. The long term goal of this research project is to develop and distribute such a conceptual data model. The implementation of the model will be supported by a multi-platform software application. The proposed application including data model and associated database will integrate the NMR data model and existing NMR data processing and analysis software (free and commercial products) to improve productivity at the data collection, data assignment, data analysis and structure determination phases. The R21 phase will focus on the data model/database design (in progress) and development of a prototype application including a Linux-based graphical user interface which will be capable of interacting with the database backend and other NMR software available for the Linux platform. During the R33 phase, a visual representation of the NMR data model will be developed for use by researchers, both to aid in learning the proposed application as well as in understanding NMR data. This representation will allow researchers to view NMR data at a range of levels of abstraction from the experiment level to the pulse-sequence level. In addition, in years 3 and 4, the software will be ported to the Mac OS X platform, with the database linked as a web-accessible backend available to both Linux and Mac clients. Documentation of the application will be completed in the R33 phase.