SBIR-STTR Award

There is currently a significant demand for proteomics software which enables rapid and accurate data analysis. The advances over recent years in proteomics instrumentation and throughput coupled with the continued expansion of biological databases has resulted is researchers being able to produce very large amounts of data in relatively short time periods. Since informatics developments have not kept pace with the advances in analytical technologies, data analysis now represents a major bottleneck in proteomics-based discoveries. Thus, there is a significant need for software which assists researchers in analyzing their complex proteomics data in a high-throughput manner. The research proposed in this application is to design an a easy to use, cross- platform software package that will allow users to 1) integrate results from multiple database search engines 2) provide statistical validation of large proteome datasets, 3) facilitate easy comparisons between proteomes, 4) quantitate protein expression between biological samples, and 5) annotate protein identifications with biological data from public databases. The integrated software package described in this proposal, once commercialized, will greatly enhance the speed and accuracy of proteomics research.The proposed studies will provide a software package which will greatly assist researchers in making use of their proteomics data. Since the proteomics field is continually growing, it is believed that the software developed here will be a valuable resource to a diverse set of researchers. Making this software available to the scientific community will increase the throughput of proteomics research and speed the discovery process.

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There is currently a significant demand for proteomics software which enables rapid and accurate data analysis. The advances over recent years in proteomics instrumentation and throughput coupled with the continued expansion of biological databases has resulted is researchers being able to produce very large amounts of data in relatively short time periods. Since informatics developments have not kept pace with the advances in analytical technologies, data analysis now represents a major bottleneck in proteomics-based discoveries. Thus, there is a considerable need for software which assists researchers in analyzing their complex proteomics data in a high-throughput manner. The goals of the phase I project, to produce a commercial-quality proteomics software platform, was extremely successful, and culminated in the commercial release of ProteoIQ version 1.0. We propose in phase II to first modify ProteoIQ such that performance is optimized and cross-platform portability is fully established. Statistical tools will be incorporated for the analysis of quantitative proteomics data obtained from clinical samples. We will then implement functionality to assist clinical proteomics researchers in comparing, filtering and quantifying protein expression across large numbers of patient samples. The result of this phase II project will be the release of four new software versions of ProteoIQ.

Public Health Relevance:
The proposed studies will provide a software package which will greatly assist researchers in making use of their proteomics data. Since the proteomics field is continually growing, it is believed that the software developed here will be a valuable resource to a diverse set of researchers. Making this software available to the scientific community will increase the throughput of proteomics research and speed the discovery process.

Public Health Relevance:
This Public Health Relevance is not available.

Thesaurus Terms:
There Are No Thesaurus Terms On File For This Project.